Abstract

Introduction

During the COVID-19 pandemic, restrictions were applied to movement and social contact, to contain the spread of the virus.^1,2 Many daily activities (e.g. shopping, entertainment, and contacting friends and family) shifted from face-to-face to remote delivery, often via the Internet. The UK NHS experienced a similar shift, both in mental^3–5 and in general healthcare.^6–8

These changes increased the demand for digital skills and led to more people using the Internet for longer, leading to estimations that in one year the UK made five years’ worth of progress in digital engagement.⁹ However, this situation also highlighted the pre-existing digital divide (i.e. inequalities in digital access and engagement in the population) and the health inequalities that may derive from it.¹⁰ People lacking digital skills might experience negative outcomes in relation to health, wellbeing, and social support, as they might struggle to access health services, Government and local authority services, and support network activities that are online.¹¹

It remains unknown whether people with SMI (e.g. a diagnosis of bipolar or psychosis-spectrum disorder) have the digital skills to adapt to this new digitalisation of services.¹² Finding the Internet too difficult or too complex to understand has been commonly reported among people with SMI as a barrier to using the Internet, both before^13–15 and during the pandemic.¹⁶ It is important to gain a deeper understanding of this issue, as digital exclusion in people with SMI might widen existing health and social inequalities. For example, people with SMI are at greater risk for long-term physical health conditions¹⁷ and at greater need for regular healthcare appointments to monitor their conditions (e.g. the annual physical health check).¹⁸ They might also be more likely to experience feelings of loneliness.¹⁹ Lack of skills to use the Internet might obstruct access to important sources of support (e.g. video-calls with health professionals or friends and family, accessing health and community-related information online, and participating in online community activities). It is important to note that the risk of exclusion due to lack of skill will probably not abate at the end of the pandemic, considering that the pandemic accelerated plans for digital healthcare to become a mainstream option in the NHS.²⁰

The EDS framework which has been adopted by the UK Department of Education defines the skills that people would need to have to fully benefit from using the Internet and digital devices,⁹ and sets the standards for all formal digital skills training programmes in the country. The framework includes three domains: Foundation Skills, Skills for Life, and Skills for Work. The Foundation Skills domain concerns basic prerequisite knowledge (e.g. knowing how to use the settings in a device or how to connect to a secure Wi-Fi network), while the other two domains concern five skill types in everyday life and in work environments, respectively: (1) Being safe, legal and confident online; (2) Communicating; (3) Problem solving; (4) Transacting; and (5) Handling information and content. Although EDS is mapped with the general UK population annually through the Lloyds Bank UK Consumer Digital Index, it has never been benchmarked in people with SMI specifically.

This article reports on the Skills and Proficiency in Digital Essential Requirements study (SPIDER) which assesses the digital skills of a sample of people with SMI amid the COVID-19 pandemic, based on the EDS framework. The primary objectives were to understand the extent to which people with SMI have EDS and how they compare to the general population, as well as to identify the areas of greatest deficit in skills and their association with key sociodemographic and health factors.

Methods

Results

Discussion

We assessed digital skills in a sample of people with SMI using the EDS framework. To our knowledge, this is the first time this benchmark measure of knowledge and skills has been applied to a sample of people who use mental health services. It is concerning that 42% (n = 105) had no Foundation Skills, lacking prerequisite knowledge to interact with digital technologies and benefit from their use. The most problematic areas were handling passwords and using device settings to improve usability. Older people, those not currently in work, those with a psychosis-spectrum disorder, and those with no Internet access at home were at greater risk of lacking Foundation Skills. More positively, among people who had Foundation skills, almost everyone had Skills for Life and Skills for Work.

Our results reveal a digital divide between our SMI sample and the general population. People with SMI in this study were twice as likely to experience a deficit in either Foundation or Life Skills (n = 114, 46.2%) compared to the general population (22%).²² During the pandemic, this might contribute to inequalities of access to digital services, including but not limited to healthcare services, due to a lack of familiarity or confidence with technology.²⁵ More worryingly, these inequalities might remain beyond the pandemic,²⁶ given that transition to digital healthcare might become a more mainstream option.^20,27 Combined with the fact that most people in our study owned a digital device (n = 214, 85.9%), this implies that access to digital devices on its own may do not mitigate digital exclusion and that many people may use their devices only for very basic things. This suggests that digital skills training programmes are needed, that will be tailored to the needs of people with SMI, to help close this gap (see, for example, Recovery Colleges athttps://imroc.org/resources/1-recovery-colleges/).

It was interesting that fewer of the working people in this study experienced a deficit in skills necessary for work, lacking either Foundation or Work Skills (n = 14, 23%), compared to the general population (52%).²² This could be a sampling issue in our study and might not be representative of the total SMI population. However, it may also be explained by the fact that employment is less common in people with SMI,^28–30 as shown by the 75.1% (n = 187) rate of unemployment in this study, and has been associated with younger age and higher educational attainment,^29,31,32 as well as less severe SMI symptoms.^29,32 All of these might help people to acquire good digital skills, and this may be directly linked with this study’s finding that employed participants were more likely to have Foundation Skills compared to those not in employment. Future studies should explore Skills for Work among people with SMI who are unemployed, as an indicative factor of their employment prospects and potential learning needs. Researchers should also seek to understand the contribution of digital skills deficits to the high unemployment rates in people with SMI (e.g. most jobs advertised online), especially in relation to other employment barriers related to SMI (e.g. ill health or stigma).

Looking further into skills deficits, we found that people with no Foundation Skills struggled the most with handling passwords and using device settings. As such, as important as it is to provide people with digital devices to tackle access issues (as happened a lot during the pandemic),³³ this should be combined with training and support for using these devices. Moreover, creating and maintaining a password is imperative to access several online services (e.g. GP services, streaming platforms, online banking, and Government online services, to name a few), so that deficits in that area may adversely affect not only people’s confidence in using these services but also to the security of their information. As these skills seem to be often missing in the general population as well,²² it is important for future studies to explore the specific barriers the SMI population might face, and how to address these from a person-centered design perspective. Among the few people who had Foundation Skills but no Skills for Life, the greatest area of deficit was problem-solving skills. Evidence suggests that lack of problem-solving skills in general, not just digital, is a common cognitive deficit found in people with schizophrenia.³⁴

We also found that people with no Foundation Skills were interested in learning more about half of the tasks they could not perform. Given that lack of interest is a commonly reported barrier to digital engagement,⁹ this suggests that people with SMI might have the motivation to learn new skills if appropriate support becomes available. Efforts to reduce the digital divide in the SMI population could include tailored training in digital skills along with confidence-building measures and measures to increase the motivation to address digital exclusion.¹³ Reducing the digital divide has the potential to reduce health inequalities. Future studies should seek to consult with those with lived experience to explore motivation in beginning and sustaining digital skills training, preference for training mode and setting, as well as barriers to engaging with web-based resources specifically related to SMI conditions (e.g. fluctuating levels of wellness, low energy and motivation, paranoid thoughts, suspiciousness and concerns about privacy and difficulty processing information;),³⁵ in order to develop accessible skills training programmes tailored to the needs of this population.

Older people in this study were less likely to have Foundation Skills, as also found in the general population.²² This is unsurprising, as age is traditionally associated with less digital engagement in SMI^14–16 and the general population^36,37 alike. People with psychosis-spectrum disorders were at greater risk for not having Foundation Skills compared to those with bipolar disorder, after adjusting for people’s age or employment status. This supports our previous findings that during the pandemic restrictions people with bipolar disorder were more likely to use the Internet a lot for their daily activities compared to people with psychosis.¹⁶ Cognitive and occupational dysfunctions that are common in schizophrenia³⁸ might not facilitate the development of digital skills. It might also be that specific SMI-related barriers to digital engagement (e.g. reduced concentration, hallucinations, or paranoid ideas^13,39) are more common in people with psychosis than bipolar disorder. Digital exclusion is becoming increasingly concentrated in vulnerable populations (including older people with SMI who are likely to be heavier users of healthcare services) leading to worse health outcomes through both direct and indirect routes.⁴⁰ The increasing use of digital technology in the delivery of health services will directly affect those who are digitally excluded as they will not be able to access services that could benefit them. This could range from accessing appointment booking systems to health-promoting services or applications, along with accessing video appointments. Given the current drive towards comprehensive digital healthcare within the NHS,²⁰ the importance of digital inclusion for health and social care should, and to some extent is, being acknowledged.⁴¹ The particular needs and barriers experienced by people with SMI should inform this wider policy context.

The SPIDER study is not free of limitations. The sample size may have been underpowered for the estimate of the logistic regression, but this analysis was exploratory. We used a non-random sample that might lead to respondent biases and limited generalisability, although the use of a sampling framework increases our confidence that we were recruiting across a good spread of the SMI population. Skills were self-evaluated by participants rather than completing objective tests. Self-evaluation might be susceptible to other fluctuating factors (e.g. current mood), as well as response and social desirability bias (e.g. n = 134, 53.8% of the sample completed the survey over the phone with a researcher). It should be noted though that organising objective tests, especially in the context of the pandemic restrictions, would present several practical challenges. Participants were also assessed on the basis of predetermined tasks, rather than personalised tasks related to the specific activities they want/need to complete in their everyday lives. However, that would affect the comparability of results across different populations and existing datasets. Regarding digital access, we did not examine whether the devices that people owned were current enough or had to be shared with other members of the household, as often happened during the pandemic.⁴² Despite the high rates of device ownership in our sample, real unobstructed access might be undermined by obsolete technologies or multiusership. Finally, in this study, we examined generic digital skills rather than skills and factors that may be more pertinent to this population and their use of digital health services (e.g. e-health literacy, online help-seeking and service use), which should be considered in future research.

Conclusion

This study highlighted deficits in digital skills in the SMI population that are worse than in the general population. This might suggest that an already socially disadvantaged population is at risk for further exclusions due to digital skills deficits, as many health services and social connections have moved to digital platforms during 2020/2021. Importantly and worryingly, this includes vital health services many of which might continue to operate digitally into the future. Services including the NHS need to be aware and have a responsibility to actively and immediately accommodate those with SMI who would prefer face-to-face rather than online contact, and whose health will likely suffer through the digital divide. In addition, further funding is needed for research into a widely available, person-centred, accessible training programme, co-produced with end-users to identify and remove barriers related to lack of digital skills.

Supplemental Material

Acknowledgments

This report is independent research supported by the National Institute for Health Research Yorkshire and Humber Applied Research Collaboration. The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care. We thank the participants in the SPIDER study and NHS mental health staff for their support with this study.

Footnotes

Contributor Information

P Spanakis, Department of Health Sciences, University of York, ARRC Building, Heslington, York YO10 5DD, UK Department of Psychology, University of Crete, Rethymnon, Greece; School of Psychology, Mediterranean College, Athens, Greece.

R Wadman, Department of Health Sciences, University of York, York, UK.

L Walker, Department of Health Sciences, University of York, York, UK.

P Heron, Department of Health Sciences, University of York, York, UK.

A Mathers, The Good Things Foundation, Sheffield, UK; Royal Society of Arts, London, UK.

J Baker, School of Healthcare, University of Leeds, Leeds, UK.

G Johnston, Independent Peer Researcher, Clackmannan, UK.

S Gilbody, Department of Health Sciences, University of York, York, UK.

E Peckham, Department of Health Sciences, University of York, York, UK.

References

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