How not to design the user experience: update 2018

In November 2014, I wrote a summary of my experience of entering research data in Researchfish. Since then, aspects of this system have improved: at least some of the most obvious bugs have been ironed out, and being able to link data from ORCID makes one tedious aspect of the task (entering data about particular publications) significantly easier. So well done to the ResearchFish team on fixing those problems. It's a pity it's still not fit for purpose, despite the number of funders who are supporting (mandating) use of this system.

The system is still designed without any consideration of how people conceptualise their research outputs – or at least, not how I do. According to ResearchFish, it takes less than a lunchbreak to enter all the data. There are two problems with this:
1. Few academics that I know have the time to take a lunch break.
2. So far, today, it has taken me longer than that just to work out a strategy for completing this multi-dimensional task systematically. It's like 3-D Sudoku, but less fun.

Even for publications, it's a two-dimensional task: select publications (e.g., from ORCID) and select grants to which they apply. But if you just do this as stated, then you get many-to-many relationships, with every publication assigned to grants that it isn't associated with as well as one(s) it is. And yes, I have tested this. So you have to decide which grant you're going to focus on, then go through the list and add those... then go around the loop (add new publications > select ORCID > search > select publications > select grant) repeatedly for all grants. Maybe there's a faster way to do it, but I haven't discovered that yet. Oh: and if you make a mistake, there isn't an easy way to correct it, so there is probably over-reporting as well as under-reporting on many grants.

I'm still trying to guess what "author not available" means in the information about a publication. My strategy for working out which paper each line refers to has been to keep Google Scholar open in parallel and search for the titles there, because those make more sense to me.

In the section on reporting key findings of a grant, when you save the entry, it returns you to the same page. Why would you want to save multiple times, rather than just moving on to the next step? Why isn't there a 'next' option? And why, when you have said there is no update on a completed grant, does it still take you to the update page? What was the point of the question?

When you're within the context of one award, and you select publications, it shows all publications for all awards (until you explicit select the option to focus on this award). Why? I'm in a particular task context...

When you're in the context of an award where you are simply a team member, you can filter by publications you've added, or by publications linked to this award, but not by publications that you've added that are also linked to this award. Those are the ones that I know about, and the ones that I want to check / update.

Having taken a coffee break, I returned to the interface to discover I had been logged out. I don't actually know my login details because the first time I logged in this morning I did so via ORCID. That option isn't available on the login page that appears after time-out. This is further evidence of poor system testing and non-existent user testing.

I could go on, but life is too short. There is no evidence of the developers having considered either conceptual design or task structures. There is no evidence that the system has actually been tested by real users who have real data entry tasks and time constraints. I really cannot comprehend how so many funders can mandate the use of a system that is so poorly designed, other than because they have the power to do so.

If the user can’t use it, it doesn’t work: focusing on buying and selling

"If the user can’t use it, it doesn’t work": This phrase, from Susan Dray, was originally addressed at system developers. It presupposes good understanding of who the intended users are and what their capabilities are. But the same applies in sales and procurement.

In hospital (and similar) contexts, this means that procurement processes need to take account of who the intended users of any new technology are. E.g., who are the intended users of new, wireless integrated glucometers or of new infusion pumps that need to have drug libraries installed, maintained... and also be used during routine clinical care? What training will they need? How will the new devices fit into (or disrupt) their workflow? Etc. If any of the intended users can’t use it then the technology doesn’t work.

I have just encountered an analogous situation with some friends. These friends are managing multiple clinical conditions (including Alzheimer’s, depression, the after-effects of a mini-stroke, and type II diabetes) but are nevertheless living life to the full and coping admirably. But recently they were sold a sophisticated “Agility 3” alarm system, comprising a box on the wall with multiple buttons and alerts, a wearable “personal attack alarm”, and two handheld controllers (as well as PIR sensors, a smoke alarm and more). They were persuaded that this would address all their personal safety and home security needs. I don’t know whether the salesperson referred directly or obliquely to any potential physical vulnerability. But actually their main vulnerability was that they no longer have the mental capacity to assess the claims of the salesperson, let alone the capacity to use any technology that is more sophisticated than an on/off switch. If the user can’t use it, it doesn’t work. By this definition, this alarm system doesn’t work. Caveat emptor, but selling a product that is meant to protect people when the net effect is to further expose their vulnerability is crass miss-selling. How ironic!

Innovation for innovation's sake?

As Director of the UCL Institute of Digital Health, my job is to envision the future. The future is fueled by innovation and vision. And there's plenty of that around. But the reality is much more challenging: as summarised in a recent blog post, most people aren't that interested in engaging with their health data (the ones who are most likely to be tracking their data are young, fit and wealthy), and most clinicians are struggling to even do their basic (reactive) jobs, without having much chance to think about the preventative (proactive) steps they might be taking to help people manage their health.

Why might this be? Innovation is creative and fun. It's also essential (without it, we'd still be wallowing around in the primordial soup). But there's a tendency for innovation to assume a world that is simpler than the real world: people who are engaged and compliant and have time to take up the innovation. Innovation tends not to engage with the inconvenient truths of real life, or to tackle the difficult and complex challenges that get in the way of simple visions.

We need a new approach to innovation: one that takes the really difficult challenges seriously, that accepts that the rate of progress may be slow, that recognises that it's much harder to change people and cultural practices than it is to change technology, but that these all need to be aligned for innovation to really work.

We need innovation that works with and for people. And we need to recognise that an important part of innovation is dealing with the inconvenient and difficult problems that seem to beset healthcare delivery, in all its forms.

Designing, documenting, buying, using: the mind-boggling hob

I have complained before about how difficult some taps are to use. These should be simple interactive objects whose design requirements are well understood by now, and yet designers keep generating new designs that work less well than previous models. Why is there so much emphasis in unnecessary innovation, as if innovation is inherently a good thing?

Ursula Martin has just introduced me to the unusable hob:

"This bizarre thing requires you to select a ring with the rotating arrow before applying plus/minus.  Now here's a thing. Suppose you have switched on ring 1 (bottom right), and no others, set it to 4 (a red 4 appears due South of the Ring 1) and a few minutes later you decide you want to turn it down to 3. How do you do that? Press the minus sign, as that is the only ring that is on? Oh no, nothing happens if you do that. it appears that you HAVE TO CYCLE THROUGH ALL THE OTHER RINGS AND BACK TO 1, then red 4 will start to flash, and then the minus/plus signs will change it. Just imagine the hoopla of doing that when you have four rings going at once."

The instruction manual is full of information like:
"Each cooking zone is equipped with an auto-
matic warm-up function. When this is activa-
ted, then the given cooking zone is switched
on at full power for a time dpending on the heat
setting selected, and is then switched back to
the heat setting set.

Activate the automatic warm-up function by
setting the required heating power by touching
the (+) sensor (5) first. Then the heating level
„9” is displayed intermittently on the cooking
zone indicator (3) with the letter “A” for around
10 seconds."

And so on, for many pages (spelling mistakes an added bonus). This is a manual that opens with the (only slightly patronising):

"DEAR USER,

The plate is exceptionally easy to use and extremely efficient. After reading the instruction manual, operating the cooker will be easy."

Ursula notes that: "The designer seems to have a mythical cook in mind who doesn’t want to change the temperature very often". Alternatively, maybe it's from the Dilbert school of design. All one can be sure about is that the design team apparently never use a hob, and that the technical authors who have written the 28-page manual on how to operate this hob were happy to write out inscrutable instructions without ever seriously considering their comprehensibility. And had apparently also never used a hob.

Finally, Ursula reported that "the flat owner is very embarrassed about it - he has just had the kitchen redone and I am the first tenant since, and he hadn’t used the thing himself". If you've ever bought a new appliance and tried to assess its usability before purchase you will probably sympathise with the landlord. It's usually impossible to test these things out before buying; to even read the manual; or to get any reliable information from the sales team about usability. In fact, ease of use, usability and fitness for purpose don't feature prominently in our discourse.

We really do need a cultural shift such that fitness for purpose trumps innovation. Don't we?

How not to design the user experience in electronic health records

Two weeks ago, I summarised my own experience of using a research reporting system. I know (from subsequent communications) that many other researchers shared my pain. And Muki Haklay pointed me at another blog on usability of enterprise software, which discusses how widespread this kind of experience is with many different kinds of software system.

Today, I've had another experience that I think it's worth reporting briefly. I had a health screening appointment with a nurse (I'll call her Naomi, but that's not her real name). I had to wait 50 minutes beyond the appointment time before I was seen. Naomi was charming and apologetic: she was struggling with the new health record system, and every consultation was taking longer than scheduled. This was apparently only the second day that she had been using the health screening functions of the system. And she clearly thought that it was her own fault that she couldn't use it efficiently.

She was shifting between different screen displays more times than I could count. She had a hand-written checklist of all the items that needed to be covered in the screening, and was using a separate note (see right) to keep track of the measurements that she was taking. She kept apologising that this was only because the system was unfamiliar, and she was sure she'd be able to work without the checklist before long. But actually, checklists are widely considered helpful in healthcare. She was working systematically, but this was in spite of the user interactions with the health record system, which provided no support whatsoever for her tasks, and seemed positively obstructive at times. As far as I know, all the information Naomi entered into my health record was accurate, but I left her struggling with the final item: even though, as far as either of us could see, she had completed all the fields in the last form correctly, the system wasn't letting her save it, blocking it with a claim that a field (unspecified) had not been completed. Naomi was about to seek help from a colleague as I left. I don't know what the record will eventually contain about my smoking habits!

This is just one small snapshot of users' experience with another system that is not fit for purpose. Things like this are happening in healthcare facilities all over the world every day of the week. The clinical staff are expected to improvise and act as the 'glue' between systems that have clearly been implemented with minimal awareness of how they will actually be used. This detracts from both the clinicians' and the patients' experiences, and if all the wasted time were costed it would probably come to billions of £/$/€/ currency-of-your-choice. Electronic health records clearly have the potential to offer many capabilities that paper records could not, but they could be so, so much better than they are if only they were designed with their users and purposes in mind.

How not to design the user experience

Thank you to ResearchFish, a system that many UK researchers are required to use to report their research outcomes, for providing a rich set of examples of user experience bloopers. Enjoy! Or commiserate...

* The ‘opening the box’ experience: forget any idea that people have goals when using the system (in my case, to enter information about publications and other achievements based on recent grants held): just present people with an array of options, most of them irrelevant. If possible, hide the relevant options behind obscure labels, in the middle of several irrelevant options. Ensure that there is no clear semantic groupings of items. The more chaotic and confused the interaction, the more of an adventure it’ll be for the user.

* The conceptual model: introduce neat ideas that have the user guessing: what’s the difference between a team member and a delegate? What exactly is a portfolio, and what does it consist of? Users love guesswork when they’re trying to get a job done.

* Leave some things in an uncertain state. In the case of ResearchFish, some data had been migrated from a previous system. For this data, paper titles seem to have been truncated and many entries only have one page number. For example. Data quality is merely something to aspire to.

* Leave in a few basic bugs. For example, there was a point when I was allegedly looking at page 6 of 8, but there was only a ‘navigate back’ button: how would I look at page 7 of 8? [I don’t believe page 7 existed, but why did it claim that there were 8 pages?]

* If ‘slow food’ is good, then surely ‘slow computing’ must be too: every page refresh takes 6-8 seconds. Imagine that you are wading through treacle.

* Make it impossible to edit some data items. Even better: make it apparently a random subset of all possible data items.

* Don’t present data in a way that makes it clear what’s in the system and what might be missing. That would make things far too routine. Give the system the apparent structure of a haystack: some superficial structure on the outside, but pretty random when you look closer.

* Thomas Green proposed a notion of ‘viscosity’ of a system: make something that is conceptually simple difficult to do in practice. One form of viscosity is ‘repetition viscosity’. Bulk uploads? No way! People will enjoy adding entries one by one. One option for adding a publication entry is by DOI. So the cycle of activity is: identify a paper to be added; go to some other system (e.g., crossref); find the intended paper there; copy the DOI; return to ResearchFish; paste the DOI. Repeat. Repeatedly.

* Of course, some people may prefer to add entries in a different way. So add lots of other (equally tedious) alternative ways of adding entries. Keep the user guessing as to which will be the fastest for any given data type.

* Make people repeat work that’s already been done elsewhere. All my publications are (fairly reliably) recorded in Google Scholar and in the UCL IRIS system. I resorted at one point to accessing crossref, which isn’t exactly easy to use itself. So I was using one unusable system in order to populate another unusable system when all the information could be easily accessed via various other systems.

* Use meaningless codes where names would be far too obvious. Every publication has to be assigned to a grant by number. I don’t remember the number of every grant I have ever held. So I had to open another window to EPSRC Grants on the Web (GOW) in order to find out which grant number corresponds to which grant (as I think about it). For a while, I was working from four windows in parallel: scholar, crossref, GOW and ResearchFish. Later, I printed out the GOW page so that I could annotate it by hand to keep track of what I had done and what remained to be done. See Exhibit A.

* Tax the user’s memory: I am apparently required to submit entries for grants going back to 2006. I’ve had to start up an old computer to even find the files from those projects. And yes, the files include final reports that were submitted at the time. But now I’m expected to remember it all.

* Behave as if the task is trivial. The submission period is 4 weeks. A reminder to submit was sent out after two weeks. As if filling in this data is trivial. I reckon I have at least 500 outputs of one kind or another. Let’s say 10 minutes per output (to find and enter all the data and wait for the system response). Plus another 30-60 minutes per grant for entering narrative data. Yay: two weeks of my life when I am expected to teach, do research, manage projects, etc. etc. too.  And that assumes that it’s easy to organize the work, which it is not. So add at least another week to that estimate.

* Offer irrelevant error messages: At one point, I tried doing a Scopus search to find my own publications to enter them. Awful! When I tried selecting one and adding it to my portfolio, the response was "You are not authorized to access this page.” Oh: that was because I had a break between doing the search and selecting the entry, so my access had timed out. Why didn’t it say that?!? 

* Prioritise an inappropriate notion of security over usability: the security risk of leaving the page unattended was infinitesimal, while the frustration of time-out and lost data is significant, and yet researchfish timed out in the time it took to get a cup of coffee. I suspect the clock on the researchfish page may have been running all the time I was using the Scopus tool, but I'm not sure about that, and if I'm right then that's a crazy, crazy was to design the system. This kind of timeout is a great way of annoying users.

* Minimise organization of data: At one point, I had successfully found and added a few entries from Scopus, but also selected a lot of duplicate entries that are already in Researchfish. There is no way to tell which have already been added. And every time the user tries to tackle the challenge a different way it’s like starting again because every resource is organized differently. I have no idea how I would do a systematic check of completeness of reporting. This is what computers should be good at; it’s unwise to expect people to do it well.

* Sharing the task across a team? Another challenge. Everything is organised by principal investigator. You can add team members, but then who knows what everyone else is doing? If three co-authors are all able to enter data, they may all try. Only one will succeed, but why waste one person’s time when you can waste that of three (or more) people?

* Hide the most likely option. There are several drop-down menus where the default answer would be Great Britain / UK, but menu items are alphabetically ordered, so you have to scroll down to state the basically-obvious. And don’t over-shoot, or you have to scroll back up again. What a waste of time! There are other menus where the possible dates start at 1940: for reporting about projects going back to 2006. That means scrolling through over 60 years to find the most probable response.

* Assume user knowledge and avoid using forcing functions: at one point, I believed that I had submitted data for one funding body; the screen icon changed from “submit” to “resubmit” to reinforce this belief. But later someone told me there was a minimum data set that had to be submitted and I knew I had omitted some of that. So I went back and entered it. And hey presto: an email acknowledgement of submission. So I hadn’t actually submitted previously despite what the display showed. The system had let me apparently-submit without blocking that. But it wasn’t a real submission. And even now, I'm not sure that I have really submitted all the data since there is still an on-screen message telling me that it's still pending on the login page.

*Do not support multi-tasking. When I submitted data for one funding body, I wanted to get on with entering data for the next. But no: the system had to "process the submission" first. I cannot work while the computer system is working.

* Entice with inconsistency. See the order of the buttons for each of several grants (left). Every set is different. There are only 6 possible permutations of the three links under each grant heading; 5 of them are shown here. It must take a special effort to program the system to be so creative. Seriously: what does this inconsistency say about the software engineering of the system?

 

* Add enticing unpredictability. Spot the difference between the two screen shots on the right. And then take a guess at what I did to cause that change. It took me several attempts to work it out myself.

I started out trying to make this blog post light-hearted, maybe even amusing. But these problems are just scratching the surface of a system that is fundamentally unusable. Ultimately I find it really depressing that such systems are being developed and shipped in the 21st Century. What will it take to get the fundamentals of software engineering and user experience embedded in systems development?

Three steps to developing a successful app

This comment is based on studies of healthcare apps, and some recent conversations I've had, but I'm guessing it applies more widely:

1. Consider what the 'added value' of the app is intended to be. 'Because it's the 21st century' and 'Because everyone uses apps' are not added value. What are the benefits to the user of doing something with an app rather than either doing it some other way or not doing it at all? Make sure there is clear added value.
2. Consider how people will fit app use into their lives. Is it meant to be used when a particular trigger event happens (e.g., the user is planning to go for a run, or isn't feeling well today), or regularly (after every meal, first thing every morning, or whatever)? How will people remember to use the app when intended? Make sure the app fits people's lives and that any reminders or messages it delivers are timely.
3. What will people's motivations for using the app be? Are there immediate intrinsic rewards or longer term benefits? Will these be apparent to users? Does there need to be an extrinsic reward, such as competing against others or gaining 'points' of some kind, or might this be counter-productive? Are there de-motivators (such as poor usability)? Make sure the app taps in to people's motivations and doesn't put obstacles in the way of people realising the envisaged rewards.

A fourth important point is to recognise that every person is different: different lifestyle, different motivations, different on many other dimensions. So there almost certainly isn't a "one size fits all" app that everyone will love and engage with. But good and appropriate design will work for at least some people.

What's the value of human factors?

I was recently in a meeting where a technologist was reporting on a situation where a team had developed a new technology to support work in a clinical setting, but when they tried to deploy it they discovered that people didn't work in the way they had expected. From a user-centred design perspective, this is Rookie Error Number 1: so basic that it is amazing that it still happens so frequently.

It was the next statement that caught me slightly off-guard: that they should have consulted the clinicians ahead of time. Yes, of course they should. But actually, that's probably not enough either. Because clinicians (like all of us) have limited understanding of, or ability to articulate, their own work. The speaker's implicit assumption was clearly that we are all fully capable of describing our work to others in the detail that they would need to be able to design to support that work. That leaves me, as a Human Factors specialist without a job!

Which of course led me to reflect on what my role in such a situation is. What is it that I, or any other HCI / Human Factors specialist brings to the situation that the clinician or the technologist doesn't? In the case of the technologist (or at least, of the technologists who feature in this story), it's a limited understanding of what we're able to articulate, or even know, about our own activities: an assumption that if you ask someone a direct question they will give you a full, frank and accurate answer. In the case of the clinician, like anyone, it's a partial understanding of their own work practices and of how to describe them to a third party.

Many moons ago, Gordon Rugg and I wrote about this in the context of eliciting people's implicit knowledge of their own work, and I'm going to paraphrase some of our own writing:

In terms of understanding what people can articulate about their work, there are three main kinds of knowledge:

• explicit knowledge (knowledge which is readily available to introspection, and that people can readily articulate);
• semi-tacit knowledge (knowledge that can be accessed by some techniques but not by others); and
• tacit knowledge (knowledge which is not accessible to introspection via any elicitation technique). 

There are various types of semi-tacit knowledge, including taken-for-granted knowledge (that is so familiar to the speaker that they will not think to mention it); front and back versions (the official version of what should happen and a more realistic account of what actually happens); and knowledge that depends on recognition rather than recall

Tacit knowledge is subdivided into compiled skills (which have become so habitualised as to be inaccessible to introspection) and implicit learning (knowledge that is tacit throughout, never having been articulated).

So there I have at least a partial answer to my existential angst: that as a Human Factors specialist, I have knowledge of how to elicit semi-tacit knowledge about people's work – and specifically about that work for the purposes of designing technology to support it. So both the technologist and the clinician have a reason to get me involved. Whew!