PCV96 - Acceptability of technological treatment and the effect of respondent characteristics on treatment preference

OBJECTIVES: Surgical and/or technological treatment such as nerve stimulation is becoming increasingly popular in the treatment of acquired ankle-foot deformity in rehabilitation medicine. It is known that the older and impaired population can be technology adverse. The purpose of this study was to determine the acceptability of invasive technological treatment to patients and healthy controls and to study the influence of respondent characteristics on the preference for treatment. METHODS: A total of 204 Respondents participated in a conjoint analysis discrete choice experiment. Ankle-foot impairment was related to either central neurological (n = 58), or peripheral neurological disease (n = 54). Healthy respondents were also included (n = 92). The amount of information on the decision problem which was provided to the healthy controls varied. A multinomial logit regression model was used to estimate part worth utilities for the attribute levels of 8 criteria (treatment duration, treatment impact, duration and ease of use of aids, complication severity and rate, comfort & cosmetics, result type and success rate on choice of treatment) with 2–4 levels and attribute importance and to study the influence of age, gender, educational level, cognitive impairment, physical impairment and extent of information provision prior to the experiment on the fit of the regression model. RESULTS: All treatment attributes have a significant influence on treatment choice. Most important are impact of treatment (20%) and duration & ease of use of aids (19%). No operation (0.46) and minimal use of aids (0.39) is preferred. Age has a significant influence (W = 4.92; p = 0.026). No effect of cognitive impairment or ankle-foot impairment was found. CONCLUSIONS: It could be concluded that 1) surgical treatment and the use of technology are considered negative aspects of treatment, and 2) age-matched healthy respondents’ preferences can be used as predictors for cognitively and physically impaired patients.