Explaining Speech Recognition and Quality of Life Outcomes in Adult Cochlear Implant Users: Complementary Contributions of Demographic, Sensory, and Cognitive Factors.
Explaining Speech Recognition and Quality of Life Outcomes in Adult Cochlear Implant Users: Complementary Contributions of Demographic, Sensory, and Cognitive Factors.
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DOI：
10.1097/mao.0000000000002682
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发表时间：
2020-08
期刊：
影响因子：
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通讯作者：
Moberly AC
中科院分区：
文献类型：
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作者：
Skidmore JA;Vasil KJ;He S;Moberly AC
成人人工耳蜗植入（CI）的结果取决于人口统计学、感觉和认知因素。然而，这些因素与不同结果类型（如语音识别与生活质量（QOL））的关系尚未被综合研究。测试了三个假设：1)感官因素对语音识别的解释最为强烈，而认知因素对生活质量的解释更为强烈。2)不同的语音识别结果域（句子与单词）和不同的生活质量域（身体功能与社会功能与心理功能）将被人口统计学、感官和认知因素差异地解释。3)将认知因素作为预测因素将比单独的人口统计学和感官预测因素更能解释结果。需要更好地了解CI结果的影响因素，以在手术前预测结果，解释手术后的结果，并定制康复努力。41名成年语言后经验CI用户被评估句子和单词识别，以及听力相关的生活质量，以及广泛的预测指标。偏最小二乘回归用于确定最能预测结果的因素。支持我们的假设，语音识别能力最强烈地依赖于感官技能，而生活质量结果需要认知、感官和人口统计学预测因素的结合。认知测量的纳入提高了解释结果的能力，主要是对生活质量的解释。解释成人CI结果的可变性需要一个广泛的评估方法。确定最重要的预测因素取决于特定的结果域，甚至是特定的兴趣度量。
Adult cochlear implant (CI) outcomes depend on demographic, sensory, and cognitive factors. However, these factors have not been examined together comprehensively for relations to different outcome types, such as speech recognition versus quality of life (QOL). Three hypotheses were tested: 1) speech recognition will be explained most strongly by sensory factors, whereas QOL will be explained more strongly by cognitive factors. 2) Different speech recognition outcome domains (sentences versus words) and different QOL domains (physical versus social versus psychological fimctioning) will be explained differentially by demographic, sensory, and cognitive factors. 3) Including cognitive factors as predictors will provide more power to explain outcomes than demographic and sensory predictors alone. A better understanding of the contributors to CI outcomes is needed to prognosticate outcomes before surgery, explain outcomes after surgery, and tailor rehabilitation efforts. Forty-one adult postlingual experienced CI users were assessed for sentence and word recognition, as well as hearing-related QOL, along with a broad collection of predictors. Partial least squares regression was used to identify factors that were most predictive of outcome measures. Supporting our hypotheses, speech recognition abilities were most strongly dependent on sensory skills, while QOL outcomes required a combination of cognitive, sensory, and demographic predictors. The inclusion of cognitive measures increased the ability to explain outcomes, mainly for QOL. Explaining variability in adult CI outcomes requires a broad assessment approach. Identifying the most important predictors depends on the particular outcome domain and even the particular measure of interest.