How people with type two diabetes in England learn about digital health technologies, and what are the barriers to access and motivators for use? A qualitative study

(T2D) a common chronic disease, with socially patterned and Digital self-care interventions have the potential to reduce health disparities, by providing personalised low-cost reusable resources that can increase access to health interventions. However, if under-served groups are unable to access or use digital technologies, digital health interventions might make no difference, or worse, exacerbate health inequity. Study aims To gain insights into how and why people with T2D access and use web-based self-care technology and how experiences vary between individuals and social groups. A purposive sample of people with experience of using a web-based intervention to help them self-care for T2D were recruited through diabetes and community groups. Semi-structured interviews were conducted in person and over the phone. Data were analysed thematically.


Abstract
Background Type 2 Diabetes (T2D) is a common chronic disease, with socially patterned incidence and severity.
Digital self-care interventions have the potential to reduce health disparities, by providing personalised low-cost reusable resources that can increase access to health interventions. However, if under-served groups are unable to access or use digital technologies, digital health interventions might make no difference, or worse, exacerbate health inequity.

Study aims
To gain insights into how and why people with T2D access and use web-based self-care technology and how experiences vary between individuals and social groups.

Methods
A purposive sample of people with experience of using a web-based intervention to help them selfcare for T2D were recruited through diabetes and community groups. Semi-structured interviews were conducted in person and over the phone. Data were analysed thematically.

Results
A diverse sample of 21 participants were interviewed. Health care practitioners were not viewed as a good source of information about Digital Health Technology (DHT) that could support T2D. Instead participants relied on their digital skills and social networks to learn about what DHT are available and helpful. The main barriers to accessing and using DHT described by the participants were availability of DHT from the NHS, cost and technical proficiency. However, some participants described how they were able to draw on social resources such as their social networks and social status to overcome these barriers. Participants were motivated to use DHT because they provided self-care support, a feeling of control over T2D, and personalised advice or feedback. The selection of technology was also guided by participants' preferences and what they valued in relation to technology and self-care support, and these in turn were influenced by age and gender.

Conclusion
This research indicates that low levels of digital skills and high cost of digital health interventions can create barriers to the access and use of DHT to support the self-care of T2D. However, social networks and social status can be leveraged to overcome some of these challenges. If digital interventions are to decrease rather than exacerbate health inequalities, these barriers and facilitators to access and use must be considered when interventions are developed and implemented. Background Type 2 Diabetes (T2D) is a common chronic disease that creates a considerable burden to patients and health services [1][2][3][4][5][6]. A diagnosis of T2D results in widespread changes in the lives of the person with the condition as well as their families [1]. By their nature, chronic conditions cause illness over long periods and their management is complex and costly [3]. There is a social gradient to chronic illness, whereby people with lower Socio-Economic Status (SES) experience both a higher incidence and greater severity of chronic disease than those with higher SES [3,7]. It has been proposed that this gradient is created by unequal access to resources, such as: knowledge, power, advantageous social connections, money, status and good quality healthcare [8][9][10][11]. People in more privileged social positions have greater access to these key resources that they can leverage to avoid risks to health and minimise the consequence of illness once it occurs [8][9][10][11]. Those in less privileged positions have fewer resources, which means they are less likely to have good control over their health and that there are greater barriers to managing illness [8-10, 12].
Digital self-care interventions are a resource that people with chronic conditions, like T2D, can use to help them to manage their condition. These interventions have the potential to reduce health disparities, by increasing access to personalised, low-cost health interventions, whilst reducing demand on an overstretched healthcare system [13][14][15]. The digital divide in terms of unequal internet access has narrowed across socio-economic and cultural groups, largely due to increased Smartphone ownership and the reduction in the cost of technology [16][17][18][19]. There is some evidence that digital self-care interventions can be acceptable and feasible in populations that are traditionally viewed as underserved by health services [20][21][22]. These interventions may also redress power imbalances between patients and Health Care Professionals (HCPs), by providing access to health information that was previously only available to clinicians [23].
However, there is some evidence that people from lower SES groups with fewer resources are less likely to access and use digital self-care interventions [24,25]. Web-based health information has been found to be variable in quality, challenging to navigate and has mostly been developed to be used for people with high-school or greater reading ability [26,27] This study was designed to explore: how and why people with T2D access and use web-based selfcare technology and how experiences vary between individuals and social groups.

Methods
The methodological orientation underpinning the study was an inductive approach drawing on aspects of grounded theory [29,30]. Ethical approval was granted from University of Bristol Faculty of Health Sciences Research Ethics Committee 27 th April 2017.

Participants
Participants were recruited from diabetes and community groups, including groups that served Black, Asian and Minority Ethnic and lower income neighbourhoods. Participants were recruited in person, via circulated email and through adverts in Diabetes UK magazine. Adults were invited to take part if they had a diagnosis of T2D, spoke and understood English, and had ever used a web-based intervention to help them self-care for their condition. The screening questionnaire is available in the Appendix, which was used to support the purposive sampling of participants. Participants were selected from different social groups and to capture a range of experiences of the use of different types of digital interventions.

Procedure
Semi-structured interviews were conducted by telephone, in participants' homes and in a diabetes unit in a hospital. The participants received both written and verbal information about the research and provided consent before the interview. The interviews were conducted by one researcher (ST) and ranged from 35 minutes to two hours 13 minutes and were transcribed verbatim.
The first 10 minutes of one telephone interview was lost because the recording device did not pick up the audio. There were no further issues with lost data. In three phone interviews family members (children and partners) were around the person being interviewed, which may have affected the content of the interview. The transcripts were not returned to the participants for comment.
The topic guide was developed using theory and evidence of the lived experience of chronic conditions, self-care and the digital divide. There were three iterations of the topic guide, with minor changes around challenges of conducting self-care activities in the context of social gatherings (version 1.0 and the final version 1.3 available in Appendix). Field notes were taken during and after interviews.

Analysis
Analysis was ongoing and iterative and began soon after data collection had started. Insights from analysis informed subsequent data collection and the topic guide was revised to reflect emerging themes from the analysis. Interviewing continued until data saturation was reached and no new data was arising in relations to the key themes. The interviews were recorded on encrypted audiorecorders and transferred to the University of Bristol secure servers where they were kept in accordance with the Data Protection Act (2018). Transcripts were anonymised, checked for accuracy and imported into NVivo for analysis. The data were analysed using the Thematic approach [31].
Some major themes were derived from theory prior to coding and further themes were derived from the data as they emerged. Three transcripts were coded by ST and were independently coded by two other authors (CC and PL). The lists of codes were reviewed in a meeting and ST, CC and PL reached a consensus on the list of themes. New themes emerging in subsequent transcripts were discussed in regular meetings with the team and the coding structure was further refined (coding tree available in Table 3 in Appendix). Participants were provided with a summary of the findings.

Personal characteristics
This study was conducted as part of ST's PhD, during which she received formal and informal training in qualitative methods and was supervised by senior academics with specialism in qualitative research (CC and PL). ST's previous qualifications were a BSc in psychology and an MSc in neuropsychology and most of her training and experience is in quantitative methods, which may have had a bearing on the conduct and the interpretation of the interviews.

Relationship with participants
There was no prior relationship with the study participants before the study commenced. Participants interviewed in person would be aware that the interviewer (ST) was a white woman, in her thirties, who is relatively affluent, with no visible disabilities and a healthy weight. All would have known that the author was a student researcher at the University of Bristol. The participants knew that the study was about the use of technology to support the self-management of T2D but did not know the author was exploring differences by SE and cultural groups.
The position taken by the ST was that digital interventions have the potential to be beneficial for people with chronic conditions and there are likely to be socio-cultural differences in the way people access and use technology.

Sample description
Twenty-seven people with T2D were eligible to enter the study, and data saturation was reached after 21 interviews. One person expressed an interest in the study but chose not to proceed because they did not feel comfortable with the University standard procedure of data storage. The sample was diverse in terms of age (median 60 years, range 29-74), gender (11 men), socioeconomic situation and household income. Two thirds had a University degree or equivalent and 17 participants identified as White British. The sample overview is in Table 1 and the individual participant profile in in Table 2 in the Appendix.
The sample was self-selecting for those who had tried using digital technology to support the management of their condition. However, not all people in the sample were technophiles. Participants ranged from those who used one intervention to those who used multiple digital interventions (up to 7), and in one case the participant had tried digital interventions but had stopped using them because she did not find them helpful (ID 24). Twelve participants were light users (≤2 intervention) and nine were heavier users (>2 interventions) of digital technology (Table 1).

Digital interventions used
Digital health interventions used included: Blood Glucose Monitors (BGMs) with apps, wearable technology (e.g. Fitbits), online access to electronic health records, diabetic specific and general health websites and apps. Most people did not use interventions designed specifically for people with diabetes, but rather used technology designed to support healthy living and social connectivity.
Wearable fitness trackers were the most commonly used intervention (16 participants) and apps that tracked nutrition or fitness (11 participants). The diabetes specific interventions were the BGMs (Dario meter, Freestyle Libre, Trueyou mini) used by ten participants (five supplied by HCPs and five purchased privately), and three different apps each used by one participant (Diabetes diary, IBG star app and Habits-South Asian specific diabetes app).
How people learned about digital interventions Instead, participants described learning about digital interventions that might support their selfmanagement through searching the internet, social networks, support groups and online communities and forums. Participants talked about how they 'googled' interventions, navigated apps stores and products and sought out expert advice. Many participants initially found out about technology through friends and family. Participants took advice on digital interventions from those whose opinions they trusted and valued, because they were friends, were perceived to have higher status, or because they appeared to have professional knowledge. One man described how he learnt about the Change for Life app through "very knowledgeable" people in the diabetes research focus group he attends: …they have a much more in-depth, er, understanding of things. And they present more problems, and ask more questions, and say things that we wouldn't dream of saying. (

In context with health services
Many participants believed that limited resources in the NHS prevented them from accessing technology to support their diabetes self-care. This came across particularly strongly in the context of BGMs. Some participants described being provided BGMs while others described how the NHS "refused to give [them] a meter" (ID 27, white male, Low Ed). Those who were not supplied monitors felt that the NHS was limiting availability of BGMs to people with T2D because of budgetary restraints or perceived need.
it's disgraceful really that these technologies, the quite basic technologies, are so blinking expensive that people feel they have to be cut. You know, things that help people self-manage.
Because as soon (…) you get better educated and self-managed things improve, but, you know, we live in a time when that doesn't count really. (ID 37, white female, High Ed) Some participants privately bought BGM and additional test strips because they were not supplied by their HCP or because they felt that the equipment provided was not adequate for their needs. Participants described having negative reactions from HCPs about their use of BGMs when they had bought one for themselves, rather than being supplied or prescribed one on the NHS. One woman talked about being frustrated with the critical response from her doctor about Freestyle Libre, who was critical because "it doesn't meet with any approval in this neck of the woods." (ID 41, white female, High Ed). One participant described not being provided with a BGM because the nurse felt having access to a BGM may mean he ended up "in an even deeper hole" with his health-related anxiety (ID 27, white male, Low Ed). However, other technology (such as digital dietary and activity aids) used to support self-care behaviours appeared to elicit more positive reactions: "I showed them [Diabetes Diary app] to a doctor (…) he thought it was an excellent idea" (ID 20, white male, Low Ed).

Barriers and facilitators to access
The main reported barriers to privately accessing Digital Health Technology (DHT) were cost and technical proficiency. However, some participants described how they were able to draw on social resources to overcome these barriers.
The cost of DHT was prohibitive for some participants. Participants described how they had considered buying expensive technology like the Freestyle Libre, but the high cost meant it was "a no-go" (ID 40, white female, low income). One woman talked about how Fitbits had become less affordable "This one was £60, that's the cheapest. Now they've gone up to about £90 I think" (ID 10, white female, low income). Some used expensive technology (such as the Freestyle Libre) but limited its use to minimise expense, only using it "when things were going to be changing" (ID 42, white male). Others described using DHT that were free to download onto their smartphones.
Participants described how access to DHT was facilitated by people in their personal networks. They talked about having access to technology such as smartphones and watches through being given "a very generous gift" (ID 41, white female, highest income) and through perks from work such as company phones that are free to use. One participant described how her personal trainer got her to use an app (MyFitnessPal) to keep a track of what she was eating to "really understand the diabetes more" (ID 37, white female, High Ed, low income). Why people select and use technology Participants were motivated to use DHT because they provided self-care support, a feeling of control over T2D, and personalised advice or feedback. The selection of technology was also guided by participants' preferences and what they valued in relation to technology and self-care support, and these in turn were influenced by age and gender.
Participants described how DHTs gave them a sense of being in control of their condition by providing self-care support and feedback. They talked about how BGMs kept them on "the straight and narrow" with the diabetic diet by providing personalised feedback, meaning "you have nowhere to hide from that evidence" of how food impacts blood glucose levels. (ID 33, white female, High Ed). Others talked about how the feedback from wearables like Fitbits had "driven" them to increase their activity levels and "change my lifestyle as a result of trying to get that 7000 steps." (ID 27, white male, Low Ed) Access to BGMs was particularly important to the participants because many felt that this technology gave them greater control over their blood glucose levels or diabetes in general. Digital interventions were valued by many participants because they felt that the personalised information provided was more beneficial than "one fits all" (ID 27) guidelines issued by HCPs and in structured education courses. Participants talked about turning to digital interventions and forums because they offered tailoring to different culturally specific needs, personal diet preferences and learning styles that were not catered for in community-based education courses and leaflets from HCPs they had experienced.  There were mixed preferences with regard to digital forums for social support. Several participants described receiving all the support they needed from online forums. Other participants talked about how people would miss out emotional support and learning from other people with diabetes, which they felt "an app doesn't replicate" (ID 29, white male, 64yrs). A few were very negative about sharing their experiences and seeking support on digital social platforms. In contrast the two younger participants in the sample (female aged 29 and male aged 31 years old) talked about the benefits of physical interventions over digital. The younger man felt that non-digital interventions increased his opportunities to make social connections and used the discussion of health apps as a conversation starter with people at the gym:

23, Asian British-Indian male, 31yrs, High Ed, lowest income)
The younger woman felt apps were not very good compared to in-person courses like LEAP and Weightwatchers "Cause the whole point is you got to be physical" (ID 24). She was the only participant that felt none of the digital interventions she had tried had been helpful for the management of diabetes. She characterised digital interventions as being for people who were already "independent in their own exercise" (ID 24). She did express the feeling that she had different requirements than others on the diabetes support course because they were much older, but she found the quick progress she made relative to the older attendees motivating:

Discussion
Summary of main findings Participants described how they: learnt about, acquired, and used technology to support the selfmanagement of their T2D. Participants rarely learned about digital interventions from HCPs and did not perceive HCPs as knowledgeable about self-care technology. Instead they sought information from their personal social networks and diabetes support groups (in person and online). The main barriers to accessing and using DHT described by the participants were availability of digital innovations from the NHS, cost and technical proficiency. However social resources such as social networks and social capital could be leveraged to overcome some of these barriers. Participants gained access to technology through their personal networks through gifts and work perks. Group membership provided benefits which included access to discounts off expensive digital interventions and being offered free samples. Social capital was used to negotiate getting replacement technology and to gain pre-launch access to apps. Participants described how a lack of digital skills could be barrier to the use of DHT, but could be overcome by drawing on support from tech buddies in their social network. Participants were motivated to use DHT because they provided self-care support and a feeling of control over T2D. They selected DHT because they provided personalised information that could be tailored to culturally specific needs, diet preferences and learning styles, and could provide social support. Some participants felt that non-digital interventions were better at providing some aspects of support for T2D management, such as 'how to' training and emotion support. drawn on to overcome barriers to accessing digital innovations that were used by participants to gain a feeling of control over their diabetes. Social capital theory addresses inequities at a community level, and proposes there is a social hierarchy in 'the ability of actors to secure benefits by virtue of membership in social networks and other social structures' [32]. This theory suggests that belonging to a social network, provides access to resources and benefits that individuals would not have on their own [33]. This study highlighted the role of membership to social groups (e.g. diabetes groups, research groups and online forums) in providing knowledge about technology and shortcuts to accessing new and helpful innovations. This demonstrates that traditional measures of deprivation such as education, occupation and household income, are not sufficient to encapsulate the resources people had available to them.
There was also some evidence of 'bridging social capital' through memberships to these groups.
Bridging is the connections that link people across different networks or social groupings (such as ethnicity, occupational class, or religion), which are responsible for the transmission of information and resources [33][34][35][36]. Bridging occurred through diabetes support groups, involvement in research groups and online forums. A clear example of this is where a man from a traditional occupational working-class background with lower education learned about technology he had 'never heard of' through others who were 'very knowledgeable' in his research group. He may not have had the opportunity to learn about these innovations through his own personal network and gained access to the knowledge of people from different occupational and educational backgrounds.

Strengths and limitations
To the authors knowledge, this is the first study to explore how people with T2D choose technology to support to the self-care and their experiences using digital technology. Double coding of a subset of interviews by two members of the team and ongoing discussion about coding structure ensured the coding scheme was robust. Multiple views of the data promote confidence in the credibility of the findings [37]. A diverse range of experiences and opposing sides of arguments were identified and presented.
Some caution should be exercised in the transferability of the findings to other settings or populations. Despite targeted efforts made to recruit a diverse sample in terms of ethnicity and religion most of the participants identified as White-British and Christian and had tertiary degrees.
Consequently, thematic analysis may not capture the range of experiences of those from minority ethnic groups. The decision to restrict interviews to English were due to a lack of resources for interpreting, and in response to challenges with conducting cross-language qualitative research [38].
However, this may have created a barrier to study entry for some groups. People who expressed an interest in the study were mostly adults >51 years who had taken an interest in technology and were engaged in the innovations. However, the participants were not all technophiles. Those who had previously used technology but were no longer using technology were also actively sought and were present in the group, as were lighter users of technology. Those who had never used technology were not included because the main aim of the study was to understand differences in experiences of using digital tools by people from different socio-cultural backgrounds. This is likely to have excluded some groups of people who have historically been found to have lower access to the internet including; older people, those from minority ethnic groups, with lower SES and those living in remote geographical regions [39,40].

Implications for future research, policy and clinical practice
This research has highlighted the limitations of using individual measures of inequalities (such as education and income) to encapsulate the social determinants of health and resources available to a person. These measures did not account for the importance of membership to social groups (e.g. diabetes groups, research groups and online forums) and how these supported access to knowledge about technology, provided shortcuts to accessing new and helpful innovations, and support to overcome issues with usability (tech buddies) [33][34][35][36]41]. Research into health inequalities should consider the important role of social and community assets in the access and use of health interventions.
The training and availability of tech buddies may reduce barriers to accessing health technology caused by a lack of knowledge about available digital interventions, and how to access and use them.
As NHS policy begins to encourage greater adoption of digital interventions, primary care HCPs with oversight of those with chronic conditions are likely to play a role in supporting people to access and use these interventions. However, in the context of growing financial and workforce pressures and considering the views of those in this study that this is not within HCP knowledge or skills, this role may be to signpost to trained 'tech buddies' in community services. People diagnosed with chronic conditions could be linked with trained 'tech buddies' who can discuss potential technological support with them, and troubleshoot issues with technology. Currently available peer support schemes, and social prescribing programmes have been found to be acceptable and beneficial for people with chronic conditions [42,43].

Conclusion
This research indicates that low levels of digital skills and high cost of some digital innovations can create barriers to the access and use of DHT to support the self-care of T2D. However, social networks and social status can be leveraged to overcome some of these challenges. If digital interventions are to decrease rather than exacerbate health inequalities, these barriers and facilitators to access and use must be considered when interventions are developed and implemented. The training and availability of tech buddies may reduce barriers to accessing health technology caused by a lack of knowledge about available digital interventions, and how to access and use them.