Table 2 Summary of preference elicitation studies

Solomon et al. 1994 [24]

To examine patient preferences for different outcomes of stroke including death

All outpatients referred to a neuro-diagnostics laboratory for ultrasound evaluation of the carotid artery

Consequences of stroke: mild, moderate and severe impairment of three types of neurological deficit: motor, language and cognitive. Descriptions for a painless fatal stroke and perfect health.

Stroke deficit types scaled in terms of severity classifications: mild, moderate and severe impairment. Scaling validity of stroke deficit types: tested by three neurologists specialized in stroke care.

Rank and scale method over a 100 point range: 100 representing perfect health and 0 representing the worst possible health state.

Age, y(mean ± SD ): 73 ± 9

Gender, % female: 45

Country: USA

No reference to how or why deficit types were identified

Gage et al. 1996 [33]

To determine how stroke and stroke prophylaxis affect quality of life using direct preference elicitation

Patients with atrial fibrillation, at least 50 years of age, could read English and who did not reside in a convalescent hospital

Mild, moderate and major stroke

Categorised by progressively more severe neurological deficit based on Modified Rankin Scale (mild - mRS 1 or 2, moderate 3 or 4, severe 4 or 5). Utilised van Hoeyweghen et al. [36] which recommended that stroke descriptions of function cover multiple domains: fine and gross motor skills, spoken and written language are, and cognitive and psychosocial function

Time trade-off and standard gamble

Age, y(mean ± SD ): 70.1 ± 7.3

Gender, % male: 86

Country: USA

Shin et al. 1997 [34]

To determine younger patients’ perceptions of quality of life with a stroke by eliciting utility values

Younger patients with arteriovenous malformations who are at risk of a stroke or have experienced one.

Major and minor stroke

No information regarding how stroke severity classifications were developed

Standard gamble

Age, y(mean)(range): 37(18-57)

Gender: not reported

Country: Canada

Samsa et al. 1998 [17]

To examine attitudes toward hypothetical major stroke

Patients at increased risk of stroke including those with and without a history of cerebrovascular symptoms but at increased risk of stroke due to conditions such as atrial fibrillation, hypertension and vascular heart disease

Major stroke with and without aphasia

No information regarding how stroke severity classifications were developed

Time trade-off

Age, y(mean): 65

Gender, % male: 52

Country: USA

Hallan et al. 1999 [14]

To elicit valid quality of life estimates and the highest acceptable treatment risk of different outcomes after stroke

Healthy people, non stroke medical patients and stroke survivors 20-84 years old

Minor and major stroke

Classifications for minor and major stroke based on Rankin scale 2-3 and 4-5 respectively

Standard gamble, time trade-off and direct scaling

Age, y(mean): not reported

Gender: not reported

Country: Norway

Robinson et al. 2001 [13]

To elicit patient valuations of health states relevant to the assessment of the prevention of stroke by warfarin anticoagulation therapy

Patients over the age of 60 years with atrial fibrillation

Mild and severe stroke as well as hospital managed warfarin and major bleed

Adapted from 2 previous studies

Standard gamble

Age, y(mean)(range): 73(60-87)

Gender, % male: 54

Country: England

Slot and Berge 2009 [35]

To ascertain patients’ preferences for thrombolytic treatment for acute stroke

Elderly people at five day care centres: ischaemic stroke survivors and age- matched control subjects who were at risk of stroke

Mild, moderately severe and severe ischaemic stroke

Based on Modified Rankin Scale for mild (mRS =1), moderately severe (mRS =3) and severe (mRS = 5) stroke

Standard gamble

Age, y(mean ± SD): 78 ± 6

Gender: not reported

Country: Norway