Although the current batteries of outcome measures have good face validity, they were not developed to measure the real-world, ecologically-valid effectiveness of cochlear implants or to uncover the underlying sources of variability responsible for the large individual differences in speech and language outcomes in this clinical population. These tests were originally selected to measure outcomes and benefits and establish device efficacy for FDA evaluation purposes. Why has there been so little progress in understanding variability and sources of individual differences in patients who receive cochlear implants? Part of the problem is that almost all of the implant centers around the world continue to use the same battery of conventional speech and language tests, with few adjustments based on developments that have taken place in closely related fields of study. Unfortunately, very little solid progress has been made in identifying the basic fundamental core underlying factors that are responsible for the variability in speech and language outcomes in this clinical population or developing new reliable predictors of outcome that move beyond the traditional routine clinical assessments that have focused almost entirely on conventional demographic, medical, educational and family variables ( Pisoni et al., 2008).
In fact, several important issues surrounding the study of variability in outcomes in both children and adults were explicitly addressed and identified as high priority areas of research in the two previous NIH Consensus Conferences on Cochlear implants held more than 15 years ago in 19 (NIH, 1988 1995). Individual differences and variability in speech and language outcomes are not new problems in the field of cochlear implantation. Moreover, the precise reasons for the enormous variability in speech and language outcomes are still unclear and remain poorly understood at this time, even after many years of clinical research on cochlear implants (see Niparko et al., 2009). However, they do not work equally well for all children and adults who receive this medical intervention. Cochlear implants work well in many hearing impaired listeners. Understanding individual differences in outcomes in this clinical population will also be critical for developing new screening methods that can be used to identify those children who may be at high risk for poor outcomes as early as possible so that novel targeted behaviorally-based interventions can be used to help children achieve optimal levels of performance from their implants and reach important speech and language milestones in development.Īt the present time, many outcome studies have been published documenting the success of cochlear implants in both children and adults (see Kirk & Choi, 2009). Why are some deaf children very successful with their cochlear implants, often achieving “near-normal” scores within the range of variation observed in typically-developing age-matched normal-hearing peers, while other children struggle and show substantial delays and weaknesses in domains such as speech perception, spoken word recognition, sentence processing, vocabulary, language and reading? Answers to these questions about the underlying factors that are responsible for the variability in speech and language outcomes following implantation have important clinical implications for improving diagnosis and treatment of children with profound hearing loss. Please note, we do not recommend using normative data in place of a control group.One of our long-term objectives is to understand and explain the enormous variability and individual differences in speech and language outcomes in deaf children who have received cochlear implants. Please contact us to discuss your normative data requirements. Outcome measures cover span length (the longest sequence successfully recalled), errors, number of attempts and latency (speed of response).
The number of boxes in the sequence increases from two at the start of the test, to nine at the end and the sequence and colour are varied through the test. The participant must then select the boxes which changed colour in the same order that they were displayed by the computer (for the forward variant) or in the reverse order (for backward variant). White squares are shown on the screen, some of which briefly change colour in a variable sequence. Spatial Span assesses visuospatial working memory capacity.
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