目标:主要目标是调查CHAPS评估听力损失患者认知能力和听觉处理的适用性,特别是在听觉处理领域,口头工作记忆,和听觉注意力。
方法:该研究包括44名年龄在7至14岁之间的人,22名听力损失(N=11名男性),22人听力正常(男性N=10)。个人听觉注意力,工作记忆,在研究中评估了听觉处理技能,并使用自我报告问卷。评估采用了持续听觉注意能力测试(SAACT),工作记忆量表(WMS),过滤词测试,听觉有像地面测试(AFGT),和儿童听觉表现量表(CHAPS)。进行了分析,包括组比较,相关性考试,和接收器工作特性(ROC)评估。
结果:CHAPS总数存在显着差异,注意,噪音,安静,和组之间的多个输入。各组间CHAPS_理想记忆和CHAPS_听觉记忆无显著差异。SAACT及其子评分的研究,WMS及其子评分,FWT,AFGT显示两组之间存在显着差异,与NH组相比,HL组中的人表现不佳。SAACT及其子得分与CHAPS_attention显着相关。AUC计算表明,SAACT和CHAPS_注意区分有或没有听力损失的人(p<0.05)。WMS_stm和WMS_total与CHAPS听觉记忆分量表相关,但是WMS_vwm没有。WMS的AUC值及其子得分在识别有或没有听力损失的儿童方面显示出显著的区别(p<0.05),而CHAPS_听觉记忆没有(AUC=0.665;p=0.060)。FWT和AFGT与CHAPS_噪声和CHAPS_多输入分量表存在显着关系。CHAPS_quiet和CHAPS_ideal子测试仅与AFGT相关。CHAPS_quite和CHAPS_ideal在识别有或没有听力损失的儿童方面没有表现出显著的判别值(p<0.05),而CHAPS_噪声,CHAPS_多个输入,FWT,AFGT做到了。
结论:CHAPS_attention分量表可能是评估听力损失儿童听觉注意力的值得信赖的工具。然而,CHAPS_听觉记忆分量表可能不适合测试工作记忆。虽然基于性能的听觉处理测试显示出更好的辨别能力,CHAPS_噪声和CHAPS_多输入子测试仍然可以评估听力受损的听觉处理。CHAPS_quiet和CHAPS_ideal子测试可能无法评估听觉处理。
OBJECTIVE: The primary goal was to investigate the suitability of CHAPS for assessing cognitive abilities and auditory processing in people with hearing loss (HL), specifically in the domains of auditory processing, verbal working memory, and auditory attention.
METHODS: The study comprised 44 individuals between the ages of seven and 14, 22 with HL (N = 11 males) and 22 with normal hearing (N = 10 males). Individuals\' auditory attention, working memory, and auditory processing skills were assessed in the study, and self-report questionnaires were used. The evaluation utilized the Sustained Auditory Attention Capacity Test (SAACT), Working Memory Scale (WMS), Filtered Words Test, Auditory Figured Ground Test (AFGT), and the Children\'s Auditory Performance Scale (CHAPS). Analyses were conducted, including group comparisons, correlation examinations, and receiver operating characteristic evaluations.
RESULTS: There were significant differences in CHAPS total, attention, noise, quiet, and multiple inputs between groups. No significant differences were seen in CHAPS_ideal and CHAPS_auditory memory across groups. The study of SAACT and its subscores, WMS and its subscores, FWT, and AFGT revealed a significant difference between groups, caused by the poor performance of persons in the HL group compared to those in the NH group. The SAACT and its subscores correlated significantly with CHAPS_attention. The AUC calculation showed that The SAACT and CHAPS_attention distinguished persons with or without HL (p < 0.05). WMS_STM and WMS_total correlated with CHAPS auditory memory subscale; however, WMS_VWM did not. AUC values for WMS and its subscores showed significant discrimination in identifying children with or without HL (p < 0.05), whereas CHAPS_auditory memory did not (AUC = 0.665; p = 0.060). FWT and AFGT had a significant relationship with CHAPS_noise and CHAPS_multiple inputs subscales. The CHAPS_quiet and CHAPS_ideal subtests only correlated with AFGT. CHAPS_quite and CHAPS_ideal did not exhibit significant discriminative values (p < 0.05) for identifying children with or without HL, while CHAPS_noise, CHAPS_multiple inputs, FWT, and AFGT did.
CONCLUSIONS: The CHAPS_attention subscale could be a trustworthy instrument for assessing auditory attention in children with HL. However, the CHAPS_auditory memory subscale may not be suitable for testing working memory. While performance-based auditory processing tests showed improved discrimination, the CHAPS_noise and CHAPS_multiple inputs subtests can still assess hearing-impaired auditory processing. The CHAPS_quiet and CHAPS_ideal subtests may not evaluate auditory processing.