Engineering lessons from the carpal tunnel syndrome “epidemic”

The fact that the widely touted carpal tunnel syndrome epidemic never materialized is an excellent example of over-hyped predictions meeting the reality of technology change.

We are swamped by predictions of future performance and technical paths, whether it involves components, circuits, systems, markets, and, of course, even diseases. The dilemma is that some of these are based on reasonably firm foundations while others are extrapolations based on some rough numbers and wishful thinking, often with a self-serving agenda. The solid results are achieved with credible tools such as Spice or COMSOL (there are many other tools, of course), while the squishy ones are done with some rough baseline numbers, nearly meaningless surveys, and the high-tech equivalent of a dartboard.

For example, back in the 1990s and early 2000s, there was a great deal of hype and even hysteria about the coming epidemic of carpal tunnel syndrome (CTS). Carpal tunnel syndrome is a condition that causes numbness, tingling, and pain in the hand and forearm. The condition occurs when one of the major nerves in the hand — the median nerve — is squeezed or compressed as it travels through the wrist (Figure 1). [Quick aside: I once heard a comic use the phrase “carpool tunnel syndrome” as a word-play to describe the misery of carpooling and getting stuck in traffic – not bad, IMO.)

Fig 1: Carpal tunnel syndrome occurs when the median nerve to the hand is squeezed or compressed as it passes through the wrist. (Image: AAOS)

Yes, CTS is a very real medical condition, no doubt of that, but it’s also often misdiagnosed and confused with other sources of pain in the same area. Still, regardless of how many sufferers there are, calling it an “epidemic” is not something I would say to describe it, yet that term was often used in connection with CTS occurrences.

So how did this presumed epidemic arise? The pundits and experts said this is due to the fact that so many people were spending all day typing at their QWERTY keyboards (Figure 2).

Fig 2: Too much keyboard typing was hyped as the major cause of this “epidemic,” but any repetitive effort can also cause it. (Image: Cleveland Clinic)

This rationale ignored the fact that the people who were really most likely to get it were those doing serious repetitive work such as bricklaying, construction, operating production equipment, working on meat-packing lines, and similar tasks rather than keyboarding.

The “panic” about the CTS epidemic was everywhere, with healthcare providers offering courses on how to avoid it, lawyers offering seminars on legal options if you got it (and for companies, how to protect against such injury lawsuits), and more. Maybe I’m a stickler here, but I think of an epidemic as related to a communicable disease, not something you bring on yourself.

Why did CTS disappear as an epidemic? It wasn’t due to herd immunity or a vaccine, that’s for sure. Instead, there were two reasons. First, many underlying assumptions about how many hours per day people used their keyboard without a break were faulty. But the second was more dramatic: the unforeseen use everywhere of touch screens (Figure 3). Even the legendary Blackberry phone with its so-called “chiclet” and prized QWERTY keyboard was not immune to the flexibility of the touch screen (Figure 4).

Fig 3: Touch screens in everything from kiosks to tablets have dramatically reduced the amount of non-stop keyboarding needed. (Image: Team Conasauga)

While the classic QWERTY keyboard is still widely used, it is no longer totally dominant as the human-machine interface (HMI) as it was assumed it would be for the foreseeable future. Kiosks, point of sale (POS) terminals, tablet screens, and many other products now use them. In short: technology took care of that “epidemic” in a way that was not anticipated.

Some – but not all – market research firms are the worst offenders in forecasting with meaningless precision. I often see reports of the market for some component or systems five years out with two and even three significant figures. Let’s be honest: any such prediction would be more credible if it came with a broad 20-30% error band rather than such meaningless precision.

Fig 4: Even the classic Blackberry phone, which dominated the market with its tiny QWERTY keyboard, was pushed aside by touch screen technology for finger-based entry. (Image: Encyclopedia Britannica)

When faced with these crystal-ball predictions, I ask obvious questions: what’s the baseline number here? What data-collection and analysis tools were used? Is the method used here meaningful, or is its role primarily to provide a veneer of credibility, which may not be justified? Is the prediction based on a simplistic extrapolation of data, or perhaps a limited survey of dubious value? Finally, I ask, “what’s in it for you?” since many of these crisis predictions are really thinly disguised pitches for more “support” and “resources” (money) for the cause.

Good engineering practice is to ask those questions and even challenge the answers. Whenever I see a forecast or prediction, I always recall the simple but insightful statement by the late baseball great Yogi Berra, who supposedly quipped, “‘It’stough to make predictions, especially about the future.” It seems to me that sums it up pretty well.

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External References