1. Poster Print Size: This poster template is 30” high by 50” wide and is printed at 120% for a 36” high by 60” wide poster. It can be used to print any poster with a 3:5 aspect ratio. Placeholders: The various elements included in this poster are ones we often see in medical, research, and scientific posters. Feel free to edit, move, add, and delete items, or change the layout to suit your needs. Always check with your conference organizer for specific requirements. Image Quality: You can place digital photos or logo art in your poster file by selecting the Insert, Picture command, or by using standard copy & paste. For best results, all graphic elements should be at least 150-200 pixels per inch in their final printed size. For instance, a 1600 x 1200 pixel photo will usually look fine up to 8“-10” wide on your printed poster. To preview the print quality of images, select a magnification of 100% when previewing your poster. This will give you a good idea of what it will look like in print. If you are laying out a large poster and using half-scale dimensions, be sure to preview your graphics at 200% to see them at their final printed size. Please note that graphics from websites (such as the logo on your hospital's or university's home page) will only be 72dpi and not suitable for printing. [This sidebar area does not print.] Change Color Theme: This template is designed to use the built-in color themes in the newer versions of PowerPoint. To change the color theme, select the Design tab, then select the Colors drop- down list. The default color theme for this template is “Office”, so you can always return to that after trying some of the alternatives. Printing Your Poster: Once your poster file is ready, visit www.genigraphics.com to order a high-quality, affordable poster print. Every order receives a free design review and we can deliver as fast as next business day within the US and Canada. Genigraphics® has been producing output from PowerPoint® longer than anyone in the industry; dating back to when we helped Microsoft® design the PowerPoint® software. US and Canada: 1-800-790-4001 Email: info@genigraphics.com [This sidebar area does not print.] The Relationship between Age, Cognitive Ability, and Listening Effort Sapna Mehta 1 ; Arlene Neuman, PhD 2, Adrienne Rubinstein, PhD 1 1 City University of New York, Department of Audiology, 2 New York University Langone Medical Center, Department of Otolaryngology Sapna Mehta City University of New York, Graduate Center Email: smehta@gradcenter.cuny.edu Contact 1.Pichora-Fuller, M. (2003). Cognitive aging and auditory information processing. International Journal of Audiology, 42, 2S26-2S32. 2.Tremblay, K., Piskosz, M., & Souza, P. (2003). Effects of age and age-related hearing loss on the neural representation of speech cues. Clinical Neurophysiology, 114(7), 1332-1343. 3.Takahashi, G., & Bacon, S. (1992). Modulation detection, modulation masking, and speech understanding in noise in the elderly. Journal of Speech, Language, and Hearing Research, 35(6), 1410-1421. 4.Akeroyd, M. A. (2008). Are individual differences in speech reception related to individual differences in cognitive ability? A survey of twenty experimental studies with normal and hearing-impaired adults. International Journal of Audiology, 47(S2), S53-S71. 5.Tun, P., McCoy, S., & Wingfield, A. (2009). Aging, hearing acuity, and the attentional costs of effortful listening. Psychology and Aging, 24(3), 761-766. 6.Pichora-Fuller, M., & Singh, G. (2006). Effects of age on auditory and cognitive processing: implications for hearing aid fitting and audiologic rehabilitation. Trends in Amplification, 10(1), 29-59. 7.Based on: Wechsler, D. (2008). Wechsler’s Adult Intelligence Scale – Fourth Edition (WAIS-IV). San Antonio, TX: Pearson. 8.Based on: Golden, C. (1978). Stroop color and word test. Wood Dale, IL: Stoelting Co. 9.For description of stimuli processing see: Kaiser A., Svirsky M. (2000, October 15-18). Using a personal computer to perform real-time signal processing in cochlear implant research. Paper presented at the Proceedings of the IXth IEEE-DSP Workshop, Hunt, TX. 10.Cohn, N. B., Dustman, R. E., & Bradford, D. C. (1984). Age‐related decrements in Stroop Color Test performance. Journal of Clinical Psychology, 40(5), 1244-1250. 11.West, R., & Alain, C. (2000). Age‐related decline in inhibitory control contributes to the increased Stroop effect observed in older adults. Psychophysiology, 37(2), 179-189. 12.Desjardins, J., & Doherty, K. (2013). Age-related changes in listening effort for various types of masker noises. Ear and Hearing, 34(3), 261-272. 13.Schurman, J., Brungart, D., & Gordon-Salant, S. (2014). Effects of masker type, sentence context, and listener age on speech recognition performance in 1-back listening tasks. The Journal of the Acoustical Society of America, 136(6), 3337-3349. Selected References Speech recognition scores: Poorer scores for the older group; F(1, 14) = 34.47, p < 0.001. Scores declined as signal to noise ratio increased; F(2, 28) = 365.94, p < 0.001 (Tukey post-hoc analysis revealed significant differences between all comparisons, p < 0.001). No significant differences in performance between the single- task and dual-task conditions. Digit recall scores: Decline in scores in the dual-task condition compared to the single-task condition; F(1, 14) = 107.43, p < 0.001. No significant main effects of age or noise condition, and no other significant interactions. Cognitive ability and digit recall scores: Poorer Stroop test interference scores for the older group (M = -0.25, SD = 3.76) compared to younger group (M = 8.12, SD = 6.64); t(14) = 2.81, p = 0.014. No significant age-related differences in digit span test scores. No significant correlations between measure of listening effort and any cognitive measure. Introduction Cognitive measures: Digit span test 7 to assess working memory capacity. Stroop test 8 to assess selective attention ability. Listening effort measures: 20 spectrally degraded vocoded AzBio sentences 9 were presented via recording. 7-digit strings were presented visually after 2 sentences. 3 noise conditions (quiet, +16 dB SNR, and +12 dB SNR) 3 task conditions (speech recognition single task, digit recall single task, sentence recognition and digit recall dual/concurrent task). Dual task condition: speech recognition was the primary task, and recall of digit strings was the secondary task. Measure of listening effort: the difference between the digit recall scores in the single and dual task conditions. Methods and Materials The following results are consistent with findings in the literature: Speech recognition scores are poorer for older adults compared to younger adults. Older adults have poorer performance on the Stroop test, suggesting poorer selective attention ability compared to younger adults 10-11. However, there are discrepancies between the findings of this study and previous research: The lack of significant findings regarding the relationship between age, noise condition, and listening effort differs from evidence in the literature 5, 12-13. No correlation was found between working memory and listening effort in this study. However, previous studies have shown a relationship between working memory and speech recognition scores 4, and working memory and listening effort when utilizing the Reading Span Test and Listening Span Test as the measures of working memory 12-13. Possible factors related to differences between the findings of this and previous studies: Small sample size and low power in this study may make it difficult to detect effects of age or noise condition on listening effort measures. Uncontrolled variables may have come from methodological issues, such as difficulty in maintaining consistent maximum performance the speech recognition tasks for some individuals, and potential variability in how the secondary (digit recall) task may have been performed from task to task. Findings regarding listening effort and age are inconclusive due to the small sample size and low power of this study. It is recommended that future studies utilize larger sample sizes to obtain adequate power in detecting effects of age and noise conditions on measures of listening effort with a dual task paradigm. Further investigation of the relationship between listening effort and the cognitive abilities of working memory and selective attention is also warranted. Use of other measures of working memory, such as the Reading Span Test or Listening Span Test may be more sensitive to a potential relationship between working memory and listening effort. It is well-documented in the literature that older adults have poorer speech recognition ability, particularly for degraded stimuli, compared to younger adults. This discrepancy may be accounted for by differences in hearing thresholds, as well as differences in the capacity for neural encoding of complex stimuli 1-3. In addition, a relationship between slower processing speed and lesser working memory capacity with lower speech recognition scores has also been found 4. The information degradation theory and effortful theory of listening suggest that humans have limited cognitive capacity for processing incoming stimuli, and when recruitment of additional cognitive resources is required for the processing of degraded inputs, performance on parallel processing or later, higher-order processing is affected 1,5-6. It is expected that when endogenous and exogenous factors lead to the degradation of auditory signals, individuals will increase utilization of cognitive resources to process and interpret the stimuli, and will expend greater effort in understanding speech. Purpose of this study: To examine the effect of age on listening effort in various background noise conditions with spectrally degraded speech stimuli, as well as explore the relationship between cognitive ability and listening effort. Results Hypotheses There is a significant effect of age on listening effort. There is a significant effect of listening condition (quiet, and different levels of background noise) on listening effort. There is a significant interaction of age and background noise condition on listening effort. There is a correlation between working memory and listening effort, and selective attention and listening effort. Participants 10 younger participants (range = 18 - 33 years, M = 24.9 years). 6 older participants (range = 58 - 64 years, M = 60.7 years). Passed the Mini Mental State Exam. Audiometric thresholds within normal limits 250 - 4000 Hz. Discussion