1 / 39

Can self-report measures reliably predict audiometric measures in Hong Kong older adults?

Can self-report measures reliably predict audiometric measures in Hong Kong older adults?. 9 Oct 2005 Kevin Yuen 12 , Michael Tong 12 , Alex Lee 12 , Peter Tang 1 , Andrew van Hasselt 12 1 Institute of Human Communicative Research, Division of Otorhinolaryngology, Dept of Surgery,

Download Presentation

Can self-report measures reliably predict audiometric measures in Hong Kong older adults?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Can self-report measures reliably predict audiometric measures in Hong Kong older adults? 9 Oct 2005 Kevin Yuen12, Michael Tong12, Alex Lee12, Peter Tang1, Andrew van Hasselt12 1Institute of Human Communicative Research, Division of Otorhinolaryngology, Dept of Surgery, The Chinese University of Hong Kong & 2Hear Talk Foundation

  2. Objectives • To compare the prevalence of hearing problem estimated from self-reports and pure-tone audiometry • To investigate the performance of self-reports: (1) a single question, (2) HHIE-S in identifying individuals with hearing loss, against the standards from pure-tone audiometry

  3. Hearing Handicap Inventory for the Elderly – Screening (HHIE-S)(Ventry & Weinstein, 1983) • Self-administered 10-item questionnaire • Aim at detecting emotional and social problems associated with impaired hearing • Subjects respond to questions about circumstances related to hearing by stating whether the situations presents a problem • “no” (score 0) • “sometimes” (score 2) • “yes” (score 4) • Total HHIE-S score range from 0 to 40

  4. HHIE-S questions (English version) • Does a hearing problem cause you to feel embarrassed when you meet new people? • Does a hearing problem cause you to feel frustrated when talking to members of your family? • Do you have difficulty hearing when someone speaks in a whisper? • Do you feel handicapped by a hearing problem? • Does a hearing problem cause you difficulty when visiting friends, relatives, or neighbors? • Does a hearing problem cause you to attend religious services less often than you would like? • Does a hearing problem cause you to have arguments with family members? • Does a hearing problem cause you to have difficulty when listening to TV or radio? • Do you feel that any difficulty with your hearing limits/hampers your personal or social life? • Does a hearing problem cause you difficulty when in a restaurant with relatives or friends?

  5. HHIE-S questions (Chinese translation version) • 在遇見新相識的人時,聽力問題有否讓你感到尷尬? • 在和家人交談時,聽力問題有否讓你感到受挫折? • 當別人喁喁細語時,你有否感到聆聽困難? • 聽力問題有否令你感到殘缺? • 聽力問題有否令你在探望朋友,家人或鄰居時感到困難? • 聽力問題有否令你參加宗教或其他活動較你希望能參加的為少? • 聽力問題有否引至你和家人或朋友吵架? • 聽力問題有否令你聆聽電視或收音機時感到困難? • 你認為任何的聽力問題有否影響你的個人或社交生活? • 和家人或朋友在餐廳時,聽力問題有否令你感到困難?

  6. Question 8 Does a hearing problem cause you to have difficulty when listening to TV or radio? 聽力問題有否令你聆聽電視或收音機時感到困難? AnswerScore “yes” ”有”4 “sometimes” “間中有”2 “no” “沒有” 0

  7. Single Question Do you think you have a problem with your hearing? 你覺得你的聽力有問題嗎?

  8. Subjects • 1016 subjects participated in the “Ear and Hearing Assessment Project for the Elderly” (June to Oct 2004) • Data from 911 subjects were analyzed in this study • 99 subjects excluded (reported signs of dementia) • 6 subjects excluded (incomplete data) • Gender distribution • Male (n=369; 40.5%); female (n=542; 59.5%)

  9. Age and gender distribution

  10. Definition of hearing loss vs hearing handicap • Hearing loss by Pure Tone Audiometry • pure tone average (PTA) of 500,1k, 2k & 4kHz of the better ear • Hearing loss defined at 4 cut-off points • PTA ≥ 25dBHL • PTA ≥ 40dBHL • PTA ≥ 55dBHL • PTA ≥ 70dBHL • Hearing handicap by HHIE-S and Single Question • HHIE-S > 8, >10, >12 & >16 • Single Question -> Answered “yes”

  11. Comparison of prevalence rates • Definition of hearing loss • PTA >25dBHL (0.5 – 4kHz) of the better ear

  12. Odds ratios for the presence of hearing loss at different PTA cut-off levels *p < 0.05, **p < 0.01, *** p < 0.0005.

  13. Prevalence of hearing loss (measured) vs hearing handicap (estimation) • Estimated prevalence • -> Single question > HHIE >8 • Prevalence from • HHIE >8 (estimation) similar to PTA ≥ 40 (measured) Hearing loss Hearing handicap 82 63 38 34 13 4

  14. Comparison of measured (audiometry) vs estimated prevalence McNemar Test p < .001 for all comparisons * except for PTA >=40 vs HHIE >8 p = .04 *

  15. Screening performance characteristics Hearing problem from HHIE-S / Single Question? Sensitivity = TP / ( TP + FN) Specificity = TN/ (TN + FP) Positive predictive value (PPV) = TP / (TP + FP) Negative predictive value (NPV) = TN/ ( TN + FN) Hearing problem from audiometry ? Positive likelihood ratio (PLR) = sensitivity/ (1-specificity) Negative likelihood ratio (NLR) = (1-sensitivity)/ specificity

  16. HHIE-S vs Single Question HHIE-S better in ruling IN the presence of hearing loss (FP) Single Question better in ruling OUT the presence of hearing loss (FN)

  17. HHIE-S vs Single Question HHIE-S better in ruling in the presence of hearing loss, with better • PPV and PLR Single Question better in ruling out the presence of hearing loss, with better • NPV and NLR

  18. HHIE >8 HHIE >16 Perfect accuracy AUC = 1 Chance AUC = 0.5 Receiving-operating characteristic curves of different PTA cut-off levels with HHIE-S score • Area undercurve (AUC) = • Discriminating power of an HHIE-S score at each PTA cut-off levels. • Probabilitythat a random person with measured hearing loss (audiometry) has a higher HHIE-S score than a random person without the hearing loss HHIE-S cutoff increase Area under curve 0.83 0.78 0.69 0.67

  19. HHIE-S > 8 vs HHIE-S > 16

  20. Revised HHIE-S cut-off score • HHIE-S > 16 vs HHIE-S > 8 • Better specificity, accuracy, (PPV) and PLR • Worse (sensitivity) • Similar NPV, NLR according to the comparisons between 95% confidence intervals For PTA cut-off levels ≥ 40 & ≥ 55 dBHL

  21. SUPER POWER SCREENER ?! Combined “HHIE-S - Single Question” screening tool P – Pass F – Fail raise sensitivity lower FN raise FP

  22. SUPER POWER SCREENING TOOL ?! HHIE-S – Single Question

  23. Conclusion 1 The prevalence of hearing handicap (HHIE-S >8) is comparable with the prevalence of hearing loss (PTA ≥ 40dBHL)

  24. Conclusion 2 The prevalence of hearing handicap increases with age. The prevalence of hearing handicap is higher in male than in female.

  25. Conclusion 3 • HHIE-S better in ruling IN the presence of hearing loss • Single Question better in ruling OUT the presence of hearing loss • HHIE-S >16 has a better screening characteristics profile than HHIE-S >8 for screening PTA level ≥ 40 and ≥ 55 dBHL

  26. Conclusion 4 For older adults reported • with hearing handicap (HHIE > 16), the probability with PTA ≥ 40dBHL is 69% (Positive predicative value). • without hearing handicap (HHIE ≤ 16), the probability with PTA < 40dBHL is 69% (Negative predicative value). Overall accuracy = 69%

  27. Kevin Yuen Division of Otorhinolaryngology, Department of Surgery The Chinese University of Hong Kong kevinyuen@surgery.cuhk.edu.hk

  28. Screening performance characteristics Hearing problem from HHIE-S / Single Question? Sensitivity = TP / ( TP + FN) Specificity = TN/ (TN + FP) Positive predictive value (PPV) = TP / (TP + FP) Negative predictive value (NPV) = TN/ ( TN + FN) Hearing problem from audiometry ? Positive likelihood ratio (PLR) = sensitivity/ (1-specificity) Negative likelihood ratio (NLR) = (1-sensitivity)/ specificity

  29. HHIE >8 HHIE >16 Receiving-operating characteristic curves of different PTA cut-off levels with HHIE-S score • Area undercurve (AUC) = • Discriminating power of an HHIE-S score at each PTA cut-off levels. • Probabilitythat a random person with measured hearing loss (audiometry) has a higher HHIE-S score than a random person without the hearing loss HHIE-S cutoff increase Area under curve 0.83 0.78 0.69 0.67

  30. Prevalence of HHIE-S >8 with age and gender Prevalence of hearing handicap increases with age Pearson Chi square = 14.2, p <.01 Linear-by-linear association = 6.3, p <.001 higher in Male than in Female Pearson Chi square = 5.2, p <.05

  31. Prevalence of HHIE >8 with degree of hearing loss Prevalence of hearing handicap increases with hearing loss Pearson Chi square = 116.8, p <.001 Linear-by-linear association = 111.1, p <.001

  32. Measured (audiometry) vs estimated prevalence – by gender

  33. Screening performance characteristics of HHIE-S and Single Question

  34. Sensitivity and specificity • Sensitivity • increase with PTA cut-off • Single question better than HHIE-S • Specificity • decrease with PTA cut-off • HHIE-S better than Single question

  35. Positive and negative predictive values (PPV & NPV) • PPV • decrease with PTA cut-off • NPV • increase with PTA cut-off

  36. Positive and negative likelihood ratios (PLR & NLR) • PLR • Increase slightly with PTA cut-off • Increase with HHIE-S cut-off • NLR • decrease with PTA cut-off • Increase slightly with HHIE-S cut-off

  37. Accuracy

More Related