Lost in the crowd? Using eye-tracking to investigate the effect of complexity on attribute non-attendance in discrete choice experiments

Table 1 Summary of participant demographics (N = 32)

Female		24/32 (75 %)
Age	mean	37.4 years
	median	32 years
	range	20–70 years
Born in Australia		17/32 (53 %)
Language spoken at home	English	28/32 (88 %)
Government concession card^a		10/32 (31 %)
Highest level of education	High school^b or vocational training	5/32 (16 %)
(Higher than 100 % due to rounding)	Undergraduate degree	15/32 (47 %)
	Postgraduate degree	12/32 (38 %)
Full-time student		5/32 16 %
Current household income^c
(Higher than 100 % due to rounding)	<$50,000	7/32 (22 %)
	$50,000- < $100,000	13/32 (41 %)
	$100,000+	12/32 (38 %)
Used vitamin last 12 months - self^d	yes	24/32 (75 %)
Used vitamin last 12 months - dr^e	yes	7/25 (22 %)
Used other CAM last 12 months^f	yes	18/32 (56 %)

^aIndicates the individual is eligible for low-income government assistance
^bYear 11 or 12 in the Australian system (final years) – no one reported a lower level
^cAustralian dollars, 2011 (before tax)
^dvitamin (self-selected) = taken a vitamin, mineral or herbal supplement not prescribed by a medical doctor in the past 12 months
^evitamin (prescribed) = taken a vitamin, mineral or herbal supplement prescribed by a medical doctor in the past 12 months
^fother CAM = used other complementary and alternative medicine products or therapies (here it includes Western herbal medicine; Chinese medicine; CAM practitioners, or indigenous or traditional folk therapies)

ISSN: 1472-6947