Applying Best-Worst scaling methodology to establish delivery preferences of a symptom supportive care intervention in patients with lung cancer
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摘要

Background

Delivering a non-pharmacological symptom management intervention in patients with lung cancer is often challenging due to difficulties with recruitment, high attrition rates, high symptom burden, and other methodological problems. The aim of the present study was to elicit quantitative estimates of utility (benefit) associated with different attribute levels (delivery options) of a symptom management intervention in lung cancer patients.

Methods

An application of Best-Worst scaling methodology was used. Effects (attributes) tested included the location of the intervention (home or hospital), type of trainer (health professional or trained volunteer), caregiver involvement or not, and intervention delivered individually or in groups of patients. Participants were asked to evaluate and compare their preferences (utilities) towards the different attribute levels within scenarios and select the pair of attribute levels that they consider to be furthest apart.

Results

Eighty-seven patients with lung cancer participated. The most important preferences for an intervention included the location (being delivered at home) and delivered by a health care professional. The least important preference was the involvement of a caregiver. Gender had an effect on preferences, with females being less inclined than men to prefer to receive an intervention in the home than the hospital and less inclined than men to have no other patients present. Furthermore, older participants and those in advanced stages of their disease were less inclined to have no other patients present compared to younger participants and those with earlier stages of disease, respectively.

Conclusion

Considering patient preferences is an important step in developing feasible, patient-centred, appropriate and methodologically rigorous interventions and this study provided indications of such patient preferences.

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