Data-gathering is under way!

What we are doing and why we are doing it

Where it all began

During a presentation by Professor Gunilla Widen on her information behaviour research, she mentioned the concept of ‘information avoidance’. My major medical condition, Type 1 diabetes, calls for a lot of data– and information-gathering by patients. Diabetes patients may need to gather data several times a day, and decide on large parts of their own treatment. But we all know that people aren’t always rational ‘information-consumers’. (Gunilla made this point very strongly.)

I began to wonder whether some people with diabetes avoid information about their conditions. If this happens, then it would be important to understand how prevalent such behaviour is. On a practical note, it would be useful to find whether and how people can be nudged into engaging with information to achieve better healthcare outcomes. I saw these questions as a possible opportunity to add to both healthcare and to information science theory.

Plotting

After discussions with colleagues within and outwith Napier, in May 2019 Dr Gemma Webster and I entered Edinburgh Napier University’s ‘Research funding competition’ with a bid for a ‘seed-project’ based on the notions above. We wanted to investigate information avoidance in diabetes, from an IT and information science viewpoint, as an example of long-term self-managed health conditions. Our colleagues in the Centre for Social informatics had peer-reviewed our draft bid, and strongly supported it. In August 2019, we were told that our bid was successful.

Impediments and benefits

After the usual set-up work, we were ready to begin substantive work. Our first impediment was tangling with NHS ethics systems [1]. Eventually we realised it would be more efficient to recruit participants via contacts within our University’s networks than to advertise online or in NHS clinics. We also didn’t want to give NHS staff extra tasks. This was made a lot easier by the University’s Research and Innovation Office putting us in contact with colleagues in the School of Health and Social Care. Also, with these colleagues, Gemma and I are currently scoping some research into the ‘real-life’ effects of alcohol on diabetes. Watch out for posts about this!

What we have done so far

Literature review

All research starts with a literature review! I began reviewing literature about information avoidance in healthcare in October 2019[2]. As we had found during the brief literature review for the funding bid, there is no research into information avoidance in diabetes. The little research so far into information avoidance in healthcare concentrates on cancer. But, to the best of my knowledge, cancer treatments and diabetes treatments are very different, not least because cancer and diabetes are very different classes of disease. For example, the impression I have is of ‘beating’ (i.e. curing) cancer. However, while it may be possible to minimise the effects of Type 2 diabetes, people who have Type 1 have an incurable condition for the rest of their lives.

Because cancer and diabetes are different classes of disease, treatment régimes are likely to be very different too, especially in terms of who decides on treatment. I’d be very surprised if cancer-patients are tasked with adjusting their own chemotherapy doses, or the frequency and intensity of their radiotherapy. In contrast, learning how to adjust their own insulin doses according to their own blood-sugar levels, carbohydrate intake and exercise is the whole point of the ‘dose-adjustment for normal eating’ (DAFNE) course for people with Type 1 diabetes. Similarly, people with Type 2 diabetes can attend ‘Diabetes Education and Self-Management for Ongoing and Newly Diagnosed’ (DESMOND) courses where they can learn to control their own blood-sugar levels.

From all of this, it appears that people with diabetes need to engage with both data and information:

  • The most important data-sets are their blood-sugar levels. Diet (especially carbohydrate intake) and exercise amounts are important too, because they strongly affect blood-sugar levels. If blood-sugar levels are high, patients may need to measure their blood-ketone levels. Many people use blood-sugar sensors[3], along with discrete meters or smart-phone apps, to find trends and other useful information from continuous monitoring of their blood-sugar data. Other people use finger-prick tests that gather snapshots of blood-sugar levels, along with paper or electronic diaries.
  • People who have diabetes need other sorts of information In general, this is information on how to live with the condition. Arguably, the most important information is on how to interpret data so that patients can decide on their own insulin doses[4]. There is information on how to adjust dose-calculations during illness. There is information on long-term management of the condition. This includes, for example, information on how to travel safely with diabetes, and on the effect of diabetes on pregnancy. There is information on the other illnesses that can be exacerbated by diabetes[5]. There is information on the serious complications that will almost certainly result from poor control of blood-sugar levels[6].

Literature review source analysis

Despite having little hope of finding much relevant material, the draft literature review cites 97 academic sources and 6 non-academic sources. Table 1 shows the full range of disciplines and sub-disciplines. Look out for a future blog-post delving into these!

Table 1: Literature-review source-analysis

Class Number in class Discipline Number in discipline Sub-discipline Number in sub-discipline
Academic 97 Economics 2 —- 2
Information Science 6 —- 5
Librarianship 1
Medical 57 —- 6
AIDS 1
Behaviour 2
Cancer 1
Communication 2
Diabetes 18
Education 1
General 1
Health 4
Information 5
Internet 1
Management 1
Nutrition 2
Paediatrics 2
Psychology 2
Social 3
Social science 3
Systems 2
Nutrition 1 —- 1
Psychology 30 —- 10
Behaviour 1
Cancer 1
Clinical 1
Health 4
Medical 4
Paediatric 1
Paediatrics 3
Social 4
Therapy 1
Risk 1 —- 1
Non-academic 6 Diabetes costs 1 —- 1
Diabetes organisation 3 —- 3
NHS 1 —- 1
Product instructions 1 —- 1
Totals 103 —- 103 —- 103

 

Develop research questions

We derived seven potential research questions from analysis of the literature. We then refined these to the following five:

  • Why may people avoid data and information about their diabetes?
  • What types of information about diabetes are avoided and used?
  • Which diabetes information channels are avoided and used?
  • How can digital diabetes information-channels be improved to get higher uptake?
  • What are the effects of adolescence on diabetes-related information behaviour?

Gathering data, and looking ahead

We developed and tested semi-structured interviews that will begin to answer these research questions. So far we have interviewed 6 young adults who have Type 1 diabetes and 4 professionals working in different roles in a diabetes clinic in a large urban hospital. Right now we’ve transcribed 5 of these. We hope to interview a few more young people. Then July will be all about analysis of what our participants have told us, then drafting articles for both academia and people with diabetes, and the professionals who help them live with the condition. Watch this space!


[1] Speaking personally, I’m a huge fan of the NHS, and of socialised medicine in general. However, the NHS can be very slow, as I found in 2016. To be fair, the NHS must be cautious about patients’ personal data.

[2] This was held up by personal circumstances taking me away from work for several months in spring 2020.

[3] I use a Freestyle Libre sensor. These used to cost me around £60 per sensor, and each lasts only 14 days. Fortunately now the NHS supplies mine. I wonder whether and how this change across NHS Lothian has changed patients’ relationships with their diabetes data.

[4] Not all patients do this. A significant number inject the same amount with each meal, and leave interpretation of blood-sugars to their doctors. (I wasn’t taught how to adjust my doses until about 8 years after I was diagnosed.)

[5] You can read about a particularly gruesome one I experienced in my personal blog.

[6] Please do not think that my relationship with my diabetes data and information is anything like good!

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