Rethinking!sound! · Fonologisk&lästräning&vid&datorn&för&döva& och&hörselskadade&barn&som&använder& cochleaimplantateller&hörapparat& & Doctoral&Thesis&No.&63&SIDR,&Linköping&University&

Rethinking sound

Computer-‐assisted reading interven5on with a phonics approach for deaf and hard of hearing children using cochlear implants or hearing aids

Tänka om ljud

Fonologisk lästräning vid datorn för döva och hörselskadade barn som använder

cochleaimplantat eller hörapparat

Doctoral Thesis No. 63 SIDR, Linköping University

Cecilia Nakeva von Mentzer PhD, SLP

Uppsala University Sweden

Linköping Studies in Arts and Science No. 627

Studies from the Swedish Institute for Disability Research No. 63

R!"#$%&$%' S()%*

Computer-assisted reading intervention with a phonics approach

for deaf and hard of hearing children using cochlear implants or hearing aids

Cecilia Nakeva von Mentzer

Cecilia Nakeva von Mentzer, Fredricia 18th of March 2015

Interdisciplinary project

Between the Swedish Disability Ins1tute, HEAD Graduate school HEaring and Deafness, Linköping University

Cogni1on, Communica1on and Learning, Lund University Karolinska University hospital, Karolinska Ins5tutet

Department of Linguis1cs, Stockholm University


Vikten av hörsel Hearing

Spoken language acquisiMon

Literacy

Academic achievement

Job opportuniMes

Background

P1 normalhörande Background

create a grand average waveform for individualsubjects. P1 was defined as the first robust positivityin the waveform. In the case of a double-peaked P1response, P1 latency was typically marked on thefirst peak. Latency values were determined for P1without regard to the chronological age and the ageof implantation of subjects.

RESULTS

Normal-Hearing ChildrenThe latency of P1 as a function of age is shown in

Figure 1. The line of best fit and the 95% confidenceinterval are superimposed on the raw data. The datawere best-fit by a growth function based on the naturallog of age (latency ! 155.6 "(-32.746)*(LN(Age));R2 ! 0.78; p # 0.0001). Visual inspection indicatesthat latencies decrease rapidly in the first decadeof life, and then decrease more gradually in thesecond decade of life. These results are consistent withthose reported by Sharma et al. (1997), Ponton et al.(2000), and Cunningham et al. (2000). As can be seenin Figure 1, P1 latency continues to decrease from 15to 20 yr of age. This finding is consistent with thatreported by Cunningham et al. (2000) who showedthat P1 latency decreased significantly from 13 to 15yr to 19 to 27 yr of age.

Children with ImplantsA 1-way ANOVA showed that the subjects in the

early, middle and late-implanted groups were notsignificantly different with respect to their durationof implant use (F ! 0.05; p ! 0.90). The latencies forthe implanted children are shown in Figure 2 as afunction of chronological age at time of testing. Thesolid functions on each plot are the 95% confidence

limits for normal-hearing children (taken from Fig.1). P1 latencies for 20 out of 21 late-implantedpersons (triangles) were outside the 95% confidencelimit for age-matched normal-hearing children. Thelatencies of 19 of the 29 children in the middle group(crosses) were outside the range of normal. In con-trast, 55 out of the 57 children in the early group(circles) had latencies within the range of normal.The proportion of latencies falling within the rangeof normal differed significantly between the early-implanted group and the late-implanted group(Fishers Exact Test for two proportions, p !0.0000001). The proportion of latencies fallingwithin the range of normal differed significantlybetween the early-implanted group and the middle-implanted group (Fishers Exact Test for two propor-tions, p ! 0.0000001). Figure 3 shows a grandaverage waveform for a subset of 18 early-implantedchildren (average age 3.8 yr) and an age-matchedgroup of normal-hearing peers (average age 3.5). A1-way ANOVA showed that the ages of the childrenin the two groups was not significantly different (F! 0.01; p ! 0.18). The average duration of implantuse for the group of 18 early implanted children was1.8 yr. As shown in Figure 3, the peak latencies of P1for the early-implanted children and their normal-hearing peers are similar. Figure 4 shows a grandaverage waveform for a subset of 13 late-implantedchildren (average age 15.1 yr) and an age-matched

Figure 1. P1 latencies as a function of age for normal-hearingchildren. The line of best-fit and the 95% confidence intervalare superimposed on the raw data. Figure 2. P1 latencies as a function of chronological age for

children with cochlear implants. The solid functions are the95% confidence limits for normal-hearing children. P1 laten-cies for children implanted before age 3.5 yr (early-implantedgroup) are shown as circles. P1 latencies for children im-planted between age 3.5 yr and 6.5 yr (middle-implantedgroup) are shown as crosses. P1 latencies for children im-planted after age 7 yr (late-implanted group) are shown astriangles.

EAR & HEARING, VOL. 23 NO. 6 535

create a grand average waveform for individualsubjects. P1 was defined as the first robust positivityin the waveform. In the case of a double-peaked P1response, P1 latency was typically marked on thefirst peak. Latency values were determined for P1without regard to the chronological age and the ageof implantation of subjects.

RESULTS

Normal-Hearing ChildrenThe latency of P1 as a function of age is shown in

Figure 1. The line of best fit and the 95% confidenceinterval are superimposed on the raw data. The datawere best-fit by a growth function based on the naturallog of age (latency ! 155.6 "(-32.746)*(LN(Age));R2 ! 0.78; p # 0.0001). Visual inspection indicatesthat latencies decrease rapidly in the first decadeof life, and then decrease more gradually in thesecond decade of life. These results are consistent withthose reported by Sharma et al. (1997), Ponton et al.(2000), and Cunningham et al. (2000). As can be seenin Figure 1, P1 latency continues to decrease from 15to 20 yr of age. This finding is consistent with thatreported by Cunningham et al. (2000) who showedthat P1 latency decreased significantly from 13 to 15yr to 19 to 27 yr of age.

Children with ImplantsA 1-way ANOVA showed that the subjects in the

early, middle and late-implanted groups were notsignificantly different with respect to their durationof implant use (F ! 0.05; p ! 0.90). The latencies forthe implanted children are shown in Figure 2 as afunction of chronological age at time of testing. Thesolid functions on each plot are the 95% confidence

limits for normal-hearing children (taken from Fig.1). P1 latencies for 20 out of 21 late-implantedpersons (triangles) were outside the 95% confidencelimit for age-matched normal-hearing children. Thelatencies of 19 of the 29 children in the middle group(crosses) were outside the range of normal. In con-trast, 55 out of the 57 children in the early group(circles) had latencies within the range of normal.The proportion of latencies falling within the rangeof normal differed significantly between the early-implanted group and the late-implanted group(Fishers Exact Test for two proportions, p !0.0000001). The proportion of latencies fallingwithin the range of normal differed significantlybetween the early-implanted group and the middle-implanted group (Fishers Exact Test for two propor-tions, p ! 0.0000001). Figure 3 shows a grandaverage waveform for a subset of 18 early-implantedchildren (average age 3.8 yr) and an age-matchedgroup of normal-hearing peers (average age 3.5). A1-way ANOVA showed that the ages of the childrenin the two groups was not significantly different (F! 0.01; p ! 0.18). The average duration of implantuse for the group of 18 early implanted children was1.8 yr. As shown in Figure 3, the peak latencies of P1for the early-implanted children and their normal-hearing peers are similar. Figure 4 shows a grandaverage waveform for a subset of 13 late-implantedchildren (average age 15.1 yr) and an age-matched

Figure 1. P1 latencies as a function of age for normal-hearingchildren. The line of best-fit and the 95% confidence intervalare superimposed on the raw data. Figure 2. P1 latencies as a function of chronological age for

children with cochlear implants. The solid functions are the95% confidence limits for normal-hearing children. P1 laten-cies for children implanted before age 3.5 yr (early-implantedgroup) are shown as circles. P1 latencies for children im-planted between age 3.5 yr and 6.5 yr (middle-implantedgroup) are shown as crosses. P1 latencies for children im-planted after age 7 yr (late-implanted group) are shown astriangles.

EAR & HEARING, VOL. 23 NO. 6 535


Background

What is phonological processing skills in spoken language?

perceive

learn new words

tell a story

play with words

read pronounce

write a story

comprehend

spell store

mentally represent speech segments

process

Par5cipants

•  Deaf and hard of hearing children DHH (N=32) – Audiological clinics at Karolinska, Lund and Uppsala University Hospital

•  Children with normal hearing, NH (N=16) –  In and outside the city of Stockholm


Inclusion/exclusion criteria for DHH 1.  Mild, moderate to severe/profound bilateral

sensorineural hearing loss 2.  Full Mme users of cochlear implants (CI) and/or

hearing aids (HA)

3.  No other disability that could affect their speech and language development and/or their cogniMve development

4.  Speak Swedish at pre-‐/school

Background variables


Beyond interven5on study

•  Development of a new method – Availability at home

•  Less travelling •  Less pressure on families


Graphogame – A phonics approach

•  InnovaMve digital based learning games •  Jyväskylä University, Nilo-‐Mäki InsMtute, Finland •  Available in different languages •  The Swedish version for beginning readers;

phonemic orthography

•  Based on the scien1fic follow-‐up study of Finnish children from birth to reading, Lyy1nen et al.


So what exactly is phonics? •  Phonics teaches the child three main things:

– Phoneme grapheme-‐correspondence – Blending – SegmenMng


Baseline 1 4 weeks Baseline 2 4 weeks Post-‐interven5on

Phonological processing & leber knowledge, 8 tasks

Same as B1 + cogniMve tasks & reading

IntervenMon Graphogame

Same as B1 + cogniMve tasks & reading

ERP: MMN N400

ERP: MMN N400

5, 6 and 7-‐ year olds

5, 6 and 7-‐ year olds, reference group

Design

Mild, Moderate to severe

hearing loss

Normally hearing children

Computer-‐assisted training

•  Children pracMced 7 min/day •  No difference regarding levels, except for age – Older children reached higher levels and accuracy

Cecilia Nakeva von Mentzer Fredricia 18th of March 2015

T

Method – Phonological composite score –  7 different accuracy measures of phonological processing skills (lower-‐–level i.e. phoneme discriminaMon, higher–level i.e. decision making about the phonemic structure of a nonword or vs. real words, and output phonology)

•  Reflect children’s general phonological processing skills

•  Enable a general comparison of the children.

– Median split –  Phonologically skilled/less skilled

Study 1 Computer-‐assisted training of phoneme-‐grapheme

correspondence for children who are deaf and hard of hearing: Effects on phonological processing skills.

Cecilia Nakeva von Mentzer1, Björn Lyxell1, Birgiba Sahlén2,6, Malin Wass1, Magnus Lindgren2,4, Marianne Ors2, Peber

Kallioinen5 & Inger Uhlén3

SLP-‐News, 2012

Interna1onal Journal of Pediatric Otorhinolaryngology, 2013


Take home message study 1 1.  Children with NH outperformed DHH children on the

majority of phonological processing tasks.

2.  All parMcipaMng children improved their accuracy in phoneme–grapheme correspondence and output phonology aper four weeks of computer-‐assisted intervenMon.

3.  For the whole group of children, and specifically for children with CI, a lower iniMal phonological composite score was associated with a larger phonological gain.

4. Eighteen DHH children whereof 11 children with CI, showed specific intervenMon effects on their phonological processing skills 5. Finally, intervenMon can be accomplished with means of a computer -‐ based program

–  Realizing this study enables studies within other groups of children

Take home message study 1


Study 2 The phonics approach in Swedish children

using cochlear implants or hearing aids: Inspecting phonological gain.

Journal of Communication Disorders, Deaf Studies &

Hearing Aids, 2014 2(3) Cecilia Nakeva von Mentzer1, Björn Lyxell1, Birgiba Sahlén2,6, Örjan

Dahlström1, Magnus Lindgren2,4, Marianne Ors2, Peber Kallioinen5 & Inger Uhlén3


Background

CogniMve processes and abiliMes are important factors to study in DHH children

– Crucial for understanding, explaining and predicMng the variability in outcomes


Background; CogniMve profiles DHH children

•  Comparable levels as NH children: Visuo-‐spaMal WM, Complex WM, InducMve reasoning

•  Reduced capacity compared to NH: Phonological working memory Lexical access



1.  DHH children performed at a lower level than NH children

on lexical access but at comparable levels on complex and visual working memory.

2.  A significant correlaMon between complex working memory and the phonological composite score was evident in DHH children but not in children with NH.


! NH D/HH D/HH, phonologically less skilled

1. Phonological change 1.0 1.0 1.0

2. Lexical access; expected answers -.58* -.36* -.43

3. Lexical access; semantically accepted .11 -.01 .07

4. Lexical access; semantically deviant .05 .04 .04

5. Lexical access; other .67** .40* .42

6. Complex WM .03 -.26 .03

7. Visual WM -.34 -.00 .12

8. Nonword repetition (pnwc) -.23 -.29 -.17

9. Nonword repetition (pcc) -.37 -.37* -.55*

10. Output phonology (pwc) .20 -.34 -.44

11. Output phonology (pcc) .21 -.38* -.51*

12. Phonological representation -.1 -.58** -.65**

13. Nonword discrimination (accuracy) -.24 -.42* -.54*

14. Nonword discrimination (latency) -.23 -.32 .24

15. Phoneme Identification (accuracy) -.49 -.29 -.12

16. Phoneme Identification (latency) -.23 -.31 -.38

17. Phonological coding–letter sounds .54* .12 .51*

18. Phonological coding–letter names .32 .06 .40*

19. Phonological coding- letter naming .21 .04 .62*

20. Nonverbal intelligence-rs .04 .03 .06

Results post interven5on


3.  Weak iniMal performance on a task for phonological representaMons was the only significant predictor of phonological change in DHH children.

4.  Weak iniMal performance was observed in children who were older when diagnosed, later implanted and in those with shorter usage-‐Mme with CI.


Take home message study 2 5.  Children with weak phonological

processing skills had addiMonal cogniMve difficulMes

6.  Leber knowledge worked as a driving force to phonological gain in children with weak phonological processing skills

Study 3

Computer-‐assisted reading intervenMon with a phonics approach for children using cochlear

implants or hearing aids Nakeva von Mentzer, C., Lyxell, B. Sahlén, B. Dahlström, Ö.,

Lindgren, M. Ors, M., Kallioinen, P. & Uhlén, I. (2013).

LogopednyJ, 2013 (4), 18-‐23. Swedish Scandinavian Journal of Psychology, 2014, 55(5), 448-‐455. doi:

10.1111/sjop.12149


Background study 3 •  A conMnuing pedagogical quesMon has been how

students who are deaf or hard of hearing opMmally develop reading ability.

•  Two pedagogical methods; “whole language” vs. “bobom-‐up” approaches, i.e., to support semanMc processing and predicMon, or to support lexical as well as sub-‐lexical processing to develop reading.


New •  We studied reading accuracy (decoding and

comprehension) as well as decoding errors.

Table 4. Decoding errors in percent (mean; ± sd, range) in reading children pre and post intervention (NH, n = 12, DHH, n = 19)

Note: NH = normal hearing, DHH = deaf and hard of hearing, an = 10 *a statistically significant difference from pre to post intervention was observed, p < .05

NH DHH

Pre Post Pre Post

TOWRE – words TOWRE – nonwords TOWRE – words and nonwords

28a ± 21.2 (1-60) 43 ± 27.6 (4-100) 40 ± 26.0 (7-83)

33 ± 24.4 (6-88) 33 ± 13.7 (12-59)* 31 ± 15.0 (11-58)*

41 ± 27.0 (5-100) 54 ± 26.0 (20-100) 47 ± 24.9 (19-87)

36 ± 21.6 (7-73) 46 ± 24.0 (5-85)* 40 ± 21.4 (13-75)*


Main message study 3 •  Age comparisons revealed a staMsMcally significant higher

reading ability in the NH 7-‐year olds compared to the DHH 7-‐year olds.

•  Reading improvement was associated with PhPS skills and complex WM in NH children.

•  Correspondent associaMons were observed with visual WM and leber naming in the DHH children.

•  DHH children’s beginning reading may be influenced by visual strategies that might cause the observed reading delay in older children.


Study 4

Segmental and suprasegmental properMes in nonword repeMMon – An exploraMve study of the associaMon with

nonword decoding in children with NH children with bilateral CI

Cecilia Nakeva von Mentzer, Björn Lyxell, Birgiba Sahlén, Örjan Dahlström,

Magnus Lindgren, Marianne Ors, Peber Kallioinen, Elisabet Engström & Inger Uhlén

Clinical Linguis1cs & Phone1cs (2014)

22 children, 6.5 years, individually matched for age

Background

•  Given their relaMvely poor phonological processing skills, researchers have someMmes claimed that children with CI read beber than what can be expected (Asker-‐Árnason, Wass, Gustavsson, Sahlén, 2014; Wass et al., 2010).

•  This pabern has also been demonstrated in studies of children with mild to moderate hearing loss (HL) (Park, Lombardino, & Riber, 2013).


? •  Do children with CI use other decoding strategies?

•  Are they more visually oriented? – Do they focus more on leber and word paberns?

– Do they develop orthographic decoding strategies earlier?


Aim •  In a more penetraMng way than previous studies we examined HOW children with CI used their phonological processing skills, as measured by nonword repeMMon, and HOW these were associated to nonword decoding

Pinpoint how the children used their phonological processing skills in phonological decoding!


Results Table 7. Correlation analysis for nonword decoding and nonword repetition in NH children (N = 11) and children with bilateral CI (N = 11)

Note: NH = normal hearing, CI = cochlear implants, * = p < .05, ** = p < .01

NONWORD DECODING

Whole words Phonemes Trials

NH CI NH CI NH CI

NO

NW

OR

D R

EPET

ITIO

N

Whole words .76** .43 .70** .33 .67** .33

Phonemes .83** .51 .76** .48 .72** .44

Consonants

Total .79** .49 .71** .50 .68** .52

No clusters .60 .51 .55 .45 .51 .39

Legal clusters .47 .42 .36 .45 .34 .48

Illegal clusters .61** .58 .57 .56 .53 .56

Vowels

Total .82** .46 .79** .36 .79** .28

No clusters .79** .54 .73** .42 .76** .32

Legal clusters .49 .33 .49 .25 .46 .25

Illegal clusters .65* .38 .60 .32 .58 .29

Syllable number .78** .50 .83** .53 .84** .57

Primary stress .24 .11 .22 .08 .24 .01


Results Table 8. Correlation analysis for nonword decoding and cluster repetition in nonwords in children with NH (N = 11) and children with CI (N =11)

Note: NH = normal hearing, CI = cochlear implants. * = p < .05, ** = p < .01.

NONWORD DECODING

Whole words Phonemes Trials

NH CI NH CI NH CI

NO

NW

OR

D R

EPET

ITIO

N

Legal clusters

Percent correct .78** .34 .77** .35 .78** .31

Consonant omissions -.55 -.66* -.51 -.59 -.55 -.40

Consonant substitutions -.45 .03 -.50 -.02 -.45 -.08

Vowel epenthesis -.45 . -.40 . -.45 .

Consonant additions . .00 . .20 . .50

Illegal clusters

Percent correct .85** .05 .88** -.01 .85** -.01

Consonant omissions -.67* .19 -.74** .35 -.74** .48

Consonant substitutions -.18 .25 -.08 .14 -.09 .12

Vowel epenthesis -.16 -.33 -.18 -.33 -.17 -.41

Consonant additions .54 .10 .59 .00 .56 .00


Summary

•  Children with CI – QualitaMvely different integraMon of phonological processing skills in nonword decoding

– Less specified phonological representaMons -‐> guessing oriented reading strategies/lexicalisaMons

– Leber knowledge seemed even more important


Clinical implica5ons

•  Phonological training should aim to improve awareness and producMon of consonant clusters and syllable structure of words. In this way, posiMve effects on phonological awareness skills will follow, as children’s phonological representaMons are improved.

•  In addiMon, leber knowledge exercises should not be overlooked since lebers act as visual support for acousMcally elusive elements in the speech signal.


General conclusions

1.  Children who are DHH consMtute a heterogeneous group. Several factors, as age at diagnosis, duraMon of unaided hearing and degree of HL contribute to the variaMon. Early intervenMon is the most crucial factor, which serves as a foundaMon for later, successful development.

2.  Overall, the results from the present thesis support the noMon that offering a computer-‐assisted intervenMon program delivered at home, is an alternaMve way to support DHH children’s phonological development and decoding proficiency.


General conclusions 3.  Specifically, children with a longer duraMon of

unaided hearing and a more severe HL benefibed comparably more from the intervenMon.

4.  The results from the present thesis may be seen as a contribuMon to fulfill the theme of UNESCO for 2014: “Equal Right, Equal Opportunity: EducaMon and Disability”. ParMcularly, by acknowledging reading ability as one of the most important tools in the educaMon of DHH children.


Thanks to... All children! ....and the research group! Björn Lyxell, BirgiJa Sahlén, Örjan Dahlström, Magnus Lindgren, Marianne Ors, PeJer Kallioinen, Elisabet Engström & Inger Uhlén

....and the conference organizersJ


Documents

Rethinking!sound! · Fonologisk&lästräning&vid&datorn&för&döva& och&hörselskadade&barn&som&använder& cochleaimplantateller&hörapparat& & Doctoral&Thesis&No.&63&SIDR,&Linköping&University&