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Ortam Sesi Tercihleri ve Dinleme Alışkanlıkları Ölçeğinin Türkçe Sürümünün (Tr-OSTDA) Geçerlik ve Güvenirlik İncelemesi

Year 2022, , 497 - 510, 31.08.2022
https://doi.org/10.21020/husbfd.1132712

Abstract

Amaç: Bu çalışmanın amacı işitme cihazı ince ayar uygulamasında kullanılmak üzere bireylerin ortam sesleri ve dinleme tercihlerini ve alışkanlıklarını değerlendirmek amacı ile Ortam Sesi Tercihleri ve Dinleme Alışkanlıkları (OST-DA) ölçeğinin Türkçe adaptasyonunu, geçerlik ve güvenirlik incelemesini normal işiten bireylerde yapmaktır. Ayrıca normal işiten (Nİ), işitme engeli olup işitme cihazı kullanamayan (İE) ve işitme cihazı kullanan (İC) bireylerde OST-DA ölçek maddeleri arasında fark olup olmadığının araştırılması da planlanmıştır.
Gereç ve Yöntem: Çalışma 18-68 yaş arası (37,73±12,89) Nİ, İE’li ve İC’li 489 katılımcı ile yürütülmüştür. OST-DA ve İşitme Engeli Ölçeği-Erişkin (İEÖ-E) Tarama ölçeği elektronik olarak uygulanmıştır.
Bulgular: OST-DA ölçeğinin Türkçe sürümünün genel Cronbach’s α ve Spearman-Brown katsayıları sırasıyla 0,90 ve 0,93 olarak bulunmuştur. Doğrulayıcı faktör analizi sonuçları χ^2=492,871,sd=209〖,χ〗^2/sd=2,358, Yaklaşık Hataların Ortalama Karekökü=0,066; Karşılaştırmalı Uyum İndeksi=0,905, Uyum İyeliği İndeksi (GFI)=0.874 olarak tespit edilmiştir. Nİ, İE’li ve İC’li grupların OST-DA skorları arasında Tek yönlü varyans analizi (ANOVA) testinde anlamlı fark bulunmuştur (p<0,01). Tukey HSD test sonuçlarına göre Nİ ve İE’li bireylerin (p<0,001) ve İE’li ve İC’li bireylerin (p<0,001) ölçek skorları arasında fark bulunmuştur.
Sonuç: OST-DA Türkçe sürümü psikometrik değerlendirmesi ölçeğin yüksek düzeyde güvenirliğe ve kabul edilebilir geçerliğe sahip olduğunu göstermektedir. OST-DA ölçeği işitme cihaz uygulamalarında uzmana bireylerin ses tercihleri ve alışkanlıkları hakkında destek bilgiler sağlayacak bir ön tarama aracı olarak klinik ve araştırma uygulamalarında kullanılabilir.

Supporting Institution

Başkent Üniversitesi

Project Number

KA21/62

References

  • Abrams, H. B., & Kihm, J. (2015). An introduction to MarkeTrak IX: A new baseline for the hearing aid market. Hearing Review, 22(6), 16.
  • Aksoy, A., Aslan, F., Köse, A., & Alpar, R. (2019). İşitme engeli ölçeği-yaşlı geçerlik ve güvenirlik: Türk popülasyonunda tarama ve uzun formlarının kullanımı. İn KBB-Forum 18(4), 310-321.
  • Almufarrij, I., Dillon, H., & Munro, K. J. (2021). Does probe-tube verification of real-ear hearing aid amplification characteristics improve outcomes in adults? A systematic review and meta-analysis. Trends in hearing, 25, 2331216521999563.
  • American Speech-Language-Hearing Association (2022). Hearing Aids for Adults (Practice Portal). available from www.asha.org/Practice-Portal/Professional-Issues/Hearing-Aids-For-Adults/
  • Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of cross-cultural psychology, 1(3), 185-216.
  • Dillon, H. (2001). Hearing Aids. (pp. 302). Sydney: Thieme.
  • Golub, J. S., Brickman, A. M., Ciarleglio, A. J., Schupf, N., & Luchsinger, J. A. (2020). Association of subclinical hearing loss with cognitive performance. JAMA Otolaryngology–Head & Neck Surgery, 146(1), 57-67.
  • Kochkin, S. (2010). MarkeTrak VIII: Consumer satisfaction with hearing aids is slowly increasing. The Hearing Journal, 63(1), 19-20.
  • Lesica, N. A. (2018). Why do hearing aids fail to restore normal auditory perception? Trends in neurosciences, 41(4), 174-185.
  • Meis, M., Huber, R., Fischer, R. L., Schulte, M., Spilski, J., & Meister, H. (2018). Development and psychometric properties of the sound preference and hearing habits questionnaire (SP-HHQ). International journal of audiology, 57(sup3), S118-S129.
  • Meister, H., Lausberg, I., Kiessling, J., Walger, M., & von Wedel, H. (2002). Determining the importance of fundamental hearing aid attributes. Otology & Neurotology, 23(4), 457-462.
  • Mondol, S. I. M. M., & Lee, S. (2019). A machine learning approach to fitting prescription for hearing aids. Electronics, 8(7), 736.
  • Nielsen, J. B., & Nielsen, J. (2013, May). Efficient individualization of hearing aid processed sound. In 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 398-402). IEEE.
  • Nkyekyer, J., Meyer, D., Blamey, P. J., Pipingas, A., & Bhar, S. (2018). Investigating the impact of hearing aid use and auditory training on cognition, depressive symptoms, and social interaction in adults with hearing loss: protocol for a crossover trial. JMIR research protocols, 7(3), e8936.
  • Søgaard Jensen, N., Hau, O., Bagger Nielsen, J. B., Bundgaard Nielsen, T., & Vase Legarth, S. (2019). Perceptual effects of adjusting hearing-aid gain by means of a machine-learning approach based on individual user preference. Trends in hearing, 23, 2331216519847413.
  • Valente, M. (2006). Guideline for audiologic management of the adult patient. Audiology Online.
  • Wolfgang, K. (2019). Artificial intelligence and machine learning: pushing new boundaries in hearing technology. The Hearing Journal, 72(3), 26-27.
  • Völker, C., Ernst, S. M., & Kollmeier, B. (2018). Hearing aid fitting and fine-tuning based on estimated individual traits. International journal of audiology, 57(sup3), S139-S145.

Validity and Reliability Analysis of the Turkish Version of the Sound Preference and Hearing Habits Questionnaire (Tr-SPHHQ)

Year 2022, , 497 - 510, 31.08.2022
https://doi.org/10.21020/husbfd.1132712

Abstract

Objectives: The aim of this study is to perform the Turkish adaptation, validity and reliability assessment of the Sound Preference and Hearing Habits Questionnaire (SP-HHQ) in normal hearing individuals. The second aim is to evaluate the sounds and listening preferences and habits of normal hearing individuals (NH), of hearing impaired but not using hearing aids (HI), and of individuals using hearing aids (HA).
Materials and Methods: This study was conducted with 489 participants aged 18-68 (37,73±12,89) with NH, HI and HA. The SP-HHQ and The Hearing Handicap Inventory for Adults was applied electronically.
Results: The general Cronbach's α and Spearman-Brown coefficients of the Turkish version of the SP-HHQ were found to be 0,90 and 0,93, respectively. The fit indexes of the model were obtained as χ^2=492,871, df=209,χ^2/ df=2,358, Root Mean Square Errors of Approximation=0,066; Comparative Fit Index=0,905, Goodness of Fit Index=0,874. A significant difference was found between the SP-HHQ scores of the NH, HI and HA groups in One-Way ANOVA test (p<0.01). According to the Tukey HSD test results, a difference was found between the scale scores of individuals with NI and IE (p<0.001) and individuals with IE and IC (p<0.001).
Conclusion: The psychometric evaluation of the Turkish version of the SP-HHQ shows that the questionnaire has high reliability and acceptable validity. The OST-DA questionnaire can be used in clinical and research settings as a preliminary screening tool that will provide information about sound preferences and habits of individuals wearing hearing aids.

Project Number

KA21/62

References

  • Abrams, H. B., & Kihm, J. (2015). An introduction to MarkeTrak IX: A new baseline for the hearing aid market. Hearing Review, 22(6), 16.
  • Aksoy, A., Aslan, F., Köse, A., & Alpar, R. (2019). İşitme engeli ölçeği-yaşlı geçerlik ve güvenirlik: Türk popülasyonunda tarama ve uzun formlarının kullanımı. İn KBB-Forum 18(4), 310-321.
  • Almufarrij, I., Dillon, H., & Munro, K. J. (2021). Does probe-tube verification of real-ear hearing aid amplification characteristics improve outcomes in adults? A systematic review and meta-analysis. Trends in hearing, 25, 2331216521999563.
  • American Speech-Language-Hearing Association (2022). Hearing Aids for Adults (Practice Portal). available from www.asha.org/Practice-Portal/Professional-Issues/Hearing-Aids-For-Adults/
  • Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of cross-cultural psychology, 1(3), 185-216.
  • Dillon, H. (2001). Hearing Aids. (pp. 302). Sydney: Thieme.
  • Golub, J. S., Brickman, A. M., Ciarleglio, A. J., Schupf, N., & Luchsinger, J. A. (2020). Association of subclinical hearing loss with cognitive performance. JAMA Otolaryngology–Head & Neck Surgery, 146(1), 57-67.
  • Kochkin, S. (2010). MarkeTrak VIII: Consumer satisfaction with hearing aids is slowly increasing. The Hearing Journal, 63(1), 19-20.
  • Lesica, N. A. (2018). Why do hearing aids fail to restore normal auditory perception? Trends in neurosciences, 41(4), 174-185.
  • Meis, M., Huber, R., Fischer, R. L., Schulte, M., Spilski, J., & Meister, H. (2018). Development and psychometric properties of the sound preference and hearing habits questionnaire (SP-HHQ). International journal of audiology, 57(sup3), S118-S129.
  • Meister, H., Lausberg, I., Kiessling, J., Walger, M., & von Wedel, H. (2002). Determining the importance of fundamental hearing aid attributes. Otology & Neurotology, 23(4), 457-462.
  • Mondol, S. I. M. M., & Lee, S. (2019). A machine learning approach to fitting prescription for hearing aids. Electronics, 8(7), 736.
  • Nielsen, J. B., & Nielsen, J. (2013, May). Efficient individualization of hearing aid processed sound. In 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 398-402). IEEE.
  • Nkyekyer, J., Meyer, D., Blamey, P. J., Pipingas, A., & Bhar, S. (2018). Investigating the impact of hearing aid use and auditory training on cognition, depressive symptoms, and social interaction in adults with hearing loss: protocol for a crossover trial. JMIR research protocols, 7(3), e8936.
  • Søgaard Jensen, N., Hau, O., Bagger Nielsen, J. B., Bundgaard Nielsen, T., & Vase Legarth, S. (2019). Perceptual effects of adjusting hearing-aid gain by means of a machine-learning approach based on individual user preference. Trends in hearing, 23, 2331216519847413.
  • Valente, M. (2006). Guideline for audiologic management of the adult patient. Audiology Online.
  • Wolfgang, K. (2019). Artificial intelligence and machine learning: pushing new boundaries in hearing technology. The Hearing Journal, 72(3), 26-27.
  • Völker, C., Ernst, S. M., & Kollmeier, B. (2018). Hearing aid fitting and fine-tuning based on estimated individual traits. International journal of audiology, 57(sup3), S139-S145.
There are 18 citations in total.

Details

Primary Language Turkish
Subjects Health Care Administration
Journal Section Articles
Authors

Asuman Alnıaçık 0000-0002-6108-7029

Eda Çakmak 0000-0002-1548-4314

Uğur Toprak 0000-0002-2949-9189

Project Number KA21/62
Publication Date August 31, 2022
Submission Date June 18, 2022
Published in Issue Year 2022

Cite

APA Alnıaçık, A., Çakmak, E., & Toprak, U. (2022). Ortam Sesi Tercihleri ve Dinleme Alışkanlıkları Ölçeğinin Türkçe Sürümünün (Tr-OSTDA) Geçerlik ve Güvenirlik İncelemesi. Hacettepe University Faculty of Health Sciences Journal, 9(2), 497-510. https://doi.org/10.21020/husbfd.1132712