首页> 外文期刊>Archives of disease in childhood >Facilitating and understanding the family's choice of injection device for growth hormone therapy by using conjoint analysis.
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Facilitating and understanding the family's choice of injection device for growth hormone therapy by using conjoint analysis.

机译:通过联合分析,促进和了解家庭对生长激素治疗的注射装置的选择。

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BACKGROUND: Conjoint analysis involves the measurement of consumer preferences between choice alternatives. AIMS AND OBJECTIVES: To investigate the use of conjoint analysis in facilitating and understanding choice of growth hormone injection devices. METHOD AND SUBJECTS: 56 patients and their parents participated in an electronic, computer-based interview. The interview took a median time of 18 min (range 12-30) and allowed an immediate matching of injection devices to the family's preferences. RESULTS: Amongst the key drivers of choice, lack of bruising was rated highest and designated an index of 100. Compared to this, the remaining attributes in order of desirability were: auto-injector (98), lack of pain (93), lightweight (88), silent (82), ready-mixed (77), ease of holding (69), telephone helpline (66), needle-free (62), small size (60), nurse support (47), hidden needle (45), stored in fridge (13) and home delivery (6). Out of the 17 families who had already chosen a device previously by discussion with the clinic nurse, the computer model placed their device either as first or second out of seven devices tested. CONCLUSION: Adaptive or interactive conjoint analysis applied at the patient level can facilitate the choice-making process whilst providing an insight into the relative importance of the key features that influence choice.
机译:背景:联合分析涉及选择备选方案之间的消费者偏好的测量。目的和目的:研究联合分析在促进和了解生长激素注射装置选择中的用途。方法和受试者:56名患者及其父母参加了电子计算机访谈。访谈的中位数时间为18分钟(范围为12-30),并允许注射设备立即与家庭的喜好相匹配。结果:在选择的关键驱动因素中,青紫的缺乏程度被评为最高,并指定为100。相比之下,按满意程度排列的其余属性是:自动注射器(98),疼痛减轻(93),轻便(88),静音(82),预混(77),易于握住(69),电话求助热线(66),无针(62),小号(60),护士支架(47),隐藏式针头(45),存放在冰箱(13)和送货上门(6)中。在先前已经通过与临床护士的讨论而选择了设备的17个家庭中,计算机模型将其设备放置为被测试的七个设备中的第一个或第二个。结论:在患者水平上进行的自适应或交互式联合分析可以促进选择过程,同时深入了解影响选择的关键特征的相对重要性。

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