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Barriers to and facilitators of the use of hearing technology, analysis model, materials and methods, the respondents’ hearing technologies, limitations, conflicts of interest.

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Assistive Hearing Technologies Among Students With Hearing Impairment: Factors That Promote Satisfaction

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Ann Mette Rekkedal, Assistive Hearing Technologies Among Students With Hearing Impairment: Factors That Promote Satisfaction, The Journal of Deaf Studies and Deaf Education , Volume 17, Issue 4, Fall 2012, Pages 499–517, https://doi.org/10.1093/deafed/ens023

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Hearing technology can play an essential part in the education of deaf and hard-of-hearing children in inclusive schools. Few studies have examined these children’s experiences with this technology. This article explores factors pertaining to children’s use of and attitudes toward hearing technologies, such as hearing aids, cochlear implants, teacher-worn microphones, and student-worn microphones. The study included 153 deaf and hard-of-hearing students. All students communicated orally and were in inclusive schools from grades 5–10. The results suggest that males view hearing technology more positively than do females. Having severe hearing loss also promoted positive attitudes toward hearing aids and cochlear implants, but not toward microphones. The students with positive self-descriptions tended to be more satisfied with hearing aids or cochlear implants than the students with negative self-descriptions. The main factors promoting the use of hearing aids were severe hearing loss, positive attitudes toward hearing aids, and the sound quality of hearing aids.

Assistive technology can be a key factor that enables individuals with disabilities to participate in daily life and be included in society ( Schneidert, Hurst, Miller, & Üstün, 2003 ). However, this technology has a double-edged nature in that it is both a tool for achieving independence and a visible sign of disability ( Scherer, 2002 ). Assistive technology that is seen as a tool or as one way of achieving desired activity is more likely to be assimilated into the user’s life. Alternatively, technology seen as a visible sign of a disability can reinforce the stigma associated with the disability. Because individuals with the latter view of technology may avoid or resist using this technology, they may avoid meaningful activities and suffer both social and physical isolation ( Polgar, 2010 ).

Hearing technologies for deaf and hard-of-hearing (DHH) individuals include personal amplifiers (e.g., hearing aids [HA] and cochlear implants [CI]), which are typically worn on the head or on the body and assistive listening devices that are not used on the head or body, such as classroom sound field amplification systems ( Dillon, 2001 ). Specialized hearing technologies may reduce the impact of barriers that DHH students experience in schools, such as classroom noise, rapid rate of discussion, rapid change of topics, and large numbers of people engaged in conversation, all of which can prevent DHH students from participating in teacher–student and student–student communication ( Luckner & Muir, 2001 ; Stinson & Antia, 1999 ). Although DHH students and their teachers report that the use of hearing technology is essential for ensuring effective inclusion ( Eriks-Brophy et al., 2006 ; Luckner & Muir, 2001 ), the equipment is sometimes used irregularly because of the stigma associated with assistive technologies.

The majority of DHH children in the western part of the world attend inclusive schools, but few findings have examined how these children view their hearing technology or how the technology is utilized. The children are infrequently asked about their experiences with hearing technology and their views on using it; scholarly attention has mainly been concentrated on the impact of personal aids on speech perceptions ( Anderson & Goldstein, 2004 ; Beadle et al., 2005 ; Iglehart, 2004 ; Loy, Warner-Czyz, Tong, Tobey, & Roland, 2010 ; Odelius, 2010 ; Yoshinaga-Itano, 1999 ). Qualitative studies on the subject have focused more on personal amplifiers and less often on assistive listening devices ( Kent & Smith, 2006 ; Preisler & Tvingstedt, 2005 ; Wheeler, Archbold, Gregory, & Skipp, 2007 ). In research on the use and nonuse of HA among children and the sense of stigma associated with HA, the respondents group have included teachers, parents, and hearing peers but not the DHH children themselves ( Blood, Blood, & Danhauer, 1978 ; Brimacombe, Danhauer, & Mulac, 1983 ; Clarke & Horvath, 1979 ; Cox, Cooper, & McDade, 1989 ; Dengerink & Porter, 1984 ; Haley Stephen & Donna, 1986 ; Ryan, Johnson, Strange, & Yonovitz, 2006 ; Silverman & Klees, 1989 ; Strange, Johnson, Ryan, & Yonovitz, 2008 ; Vesterager & Parving, 1995 ). In contrast, numerous studies have examined adults with hearing disabilities and their attitudes, feelings of stigma and qualities of life in terms of using or not using HA ( Arnold & MacKenzie, 1998 ; Bertoli et al., 2009 ; Bisgaard, 2008 ; Cameron et al., 2008 ; Cohen, Labadie, Dietrich, & Haynes, 2004 ; Laplante-Levesque, Hickson, & Worrall, 2010 ; Öberg, 2008 ; Wong, Hickson, & McPherson, 2009 ). Children who are fitted with HA or CI in early childhood may integrate such aids into their daily lives ( Preisler & Tvingstedt, 2005 ). If so, this trend might explain why there is less focus on children’s use of HA and CI compared with adults who have acquired hearing loss.

The hearing technology offered to DHH children in inclusive schools can consist of assistive listening devices, including teacher-worn microphones and student-worn microphones used by hearing classmates. Teachers and students must make daily use of the equipment. Their attitudes toward hearing technologies may affect the degree of usage and, accordingly, the level of participation in school. This article presents DHH children’s attitudes toward the different hearing technologies offered and explores predictors that can affect the children’s attitudes toward these technologies and their utilization. A comprehensive understanding of the factors affecting the utilization of HA can improve rehabilitation interventions provided by health personnel and itinerant educators both at school and at home.

Factors that can improve attitudes toward and the use of hearing technology have been related to DHH individuals themselves, the environments, and the technology ( Coniavitis-Gellerstedt, 2006 ; Craddock, 2006 ; Eriks-Brophy et al., 2006 ; Vesterager & Parving, 1995 ; Wennergren, 2008 ; Winn, 2006 ).

Personal factors, such as psychosocial factors, gender, age, and degree of hearing loss, are highlighted as important issues. Several research projects have pointed to stigma as an essential factor affecting DHH persons’ refusals to wear HA ( Bisgaard, 2008 ; Blood, Blood, & Danhauer, 1977 ; Hétu, 1996 ; Hétu, Jones, & Getty, 1993 ; Öberg, 2008 ). Individuals with HA are evaluated more negatively by teachers, parents, and hearing peers on dimensions such as intelligence, achievement, and personality through a phenomenon known as “the hearing aid effect,” which has been confirmed by a number of research studies ( Blood et al., 1978 ; Brimacombe et al., 1983 ; Cameron et al., 2008 ; Cienkowski & Pimentel, 2001 ; Cox et al., 1989 ; Dengerink & Porter, 1984 ; Haley Stephen & Donna, 1986 ; Johnson et al., 2005 ; Ryan et al., 2006 ; Silverman & Klees, 1989 ). The feelings of shame and guilt attached to hearing loss can lead to a fear of disclosing one’s hearing impairment ( Hétu, 1996 ).

In line with the stigma concept, Kent and Smith (2006 ) argue that the feeling of “being normal” is fundamental. Students who are able to perceive their use of HA in a given context as a normal phenomenon are likely to use them more frequently. Conversely, if HA use is perceived as abnormal, usage is often disguised or negated. Consequently, DHH students who express high levels of personal adjustment and willingness to use assistive hearing devices are found to have a strong sense of “being normal.” Students who struggle to participate and are reluctant users of HA, tend to view themselves as “not normal.” The study comprised 16 hearing-impaired children, between 12 and 17 years of age ( Kent & Smith, 2006 ). The normality aspect also appears in studies of children’s views of CI; Preisler and Tvingstedt (2005 ) concluded that the majority of the children in the study considered their CI to be natural parts of their lives. Wheeler et al. (2007) produced similar results and described the children as being completely depended on CI to hear; the researchers reported that the children would feel bereft if the CI could not be used.

Other psychosocial characteristics of successful hearing aid users include self-confidence, self-esteem, extroversion, and locus of control ( Brooks & Hallam, 1998 ; Cienkowski & Pimentel, 2001 ; Garstecki, 1996 ; Garstecki & Erler, 1998 ; A. S. Helvik et al., 2006 ; Humes, Wilson, & Humes, 2003 ; Kricos, Erdman, Bratt, & Williams, 2007 ; Lockey, Jennings, & Shaw, 2010 ). DHH individuals with high self-confidence, self-esteem, or extroversion are more likely to be constant HA users.

Studies have also pointed to gender as a central factor but the results have been divergent. According to Garstecki and Earler (1998) , females seem more likely than males to acknowledge their hearing loss and to use personal amplification devices. Similar conclusions were produced by studies undertaken in Switzerland and in the United Kingdom; women tended to use HA more regularly ( Bertoli et al., 2009 ; Smeeth et al., 2002 ). A Swedish study also found that, in a sample population of 595 students, girls seemed to use HA to a greater extent than boys ( Coniavitis-Gellerstedt, 2006 ). In contrast, a Norwegian study concluded that elderly males tended to experience fewer barriers to HA use than elderly females ( Solheim, 2011 ).

The degree of hearing loss has been found to predict use or nonuse of HA ( Bertoli et al., 2009 ; Clarke & Horvath, 1979 ; Kochkin, 2009 ; Smeeth et al., 2002 ; Solheim, 2011 ). According to two older studies, children with profound or mild hearing loss make less use of HA than children who have moderate or severe hearing loss ( Clarke & Horvath, 1979 ; Vesterager & Parving, 1995 ). Vesterager and Parving’s study included children with profound hearing loss who were using HA. A newer study by Kochkin (2009 ) drew a similar conclusion; based on a sample of 5000 DHH adults and children, moderate or severe hearing loss was a common characteristic of the HA users.

In addition, older DHH students seem to be less willing to use HA ( Clarke & Horvath, 1979 ; Coniavitis-Gellerstedt, 2006 ; Wennergren, 2008 ; Winn, 2006 ). Wennegren’s (2008) study concluded that nonuse of HA appeared only among the oldest students, who comprised 165 members of the sample. Winn (2006 ) found that among the 60 participants in his study, there was a progressive decline in the use of HA starting from elementary school and continuing through high school. In a research project involving students ranging from 13 to 19 years old, few HA users were found in high schools, whereas a higher number of HA users were seen in elementary schools ( Coniavitis-Gellerstedt, 2006 ). Older students also tended to use assistive listening devices less frequently than their younger counterparts ( Kent & Smith, 2006 ; Wennergren, 2008 ; Odelius, 2010 ). According to Kent and Smith (2006 ), older students have developed enhanced listening strategies and no longer need microphones.

The age of onset is also claimed to influence the utilization of HA. Early intervention is said to promote more frequent wearing of HA later in life ( Gillies, 1997 ). Another finding supports this claim, which suggests that students fitted with HA early in life appreciated their use more than those who were fitted with HA later on ( Rekkedal, 2007 ). A study of adolescents using CI showed that 38% of those implanted with CI later in life did not wish to be implanted again if their systems failed. None of the adolescent undergoing early intervention with CI shared this view ( Wheeler et al., 2007 ). In contrast, Vesterager and Parving (1995 ) did not find a relationship between early interventions with HA and use of HA, among the 76 children who participated in their study where the maximum age of onset was 10 years.

Environmental factors such as type of school attended have been associated with the utilization of HA ( Clarke & Horvath, 1979 ; Vesterager & Parving, 1995 ). Students attending special schools for DHH children use HA more irregularly than DHH children in ordinary schools ( Clarke & Horvath, 1979 ). The form of communication preferred by DHH children, such as sign or oral language, has also been related to the utilization of HA ( Cameron et al., 2008 ). Another factor reported by Kent and Smith (2006 ) is the level of support provided by friends and families. Those who perceived affirming or accepting attitudes in their relationships with family and friends were more comfortable with wearing hearing aids.

Technological factors, such as outdated technology or technology in poor working order, seem to hinder utilization ( Eriks-Brophy et al., 2006 ; Luckner & Muir, 2001 ; Wennergren, 2008 ). A Swedish study reported that 14% of inductive loop controls did not function properly ( Björklund & Sundelin, 2010 ). Similar results were found in a Norwegian study; approximately 14% of the listening devices were either out of order or used incorrectly ( Rekkedal, 2007 ).

The type of technology and sound quality are also discussed. The past decade has brought tremendous advances in hearing technology ( Lockey et al., 2010 ). As analogue technology has given way to the digital revolution, the arrival of digital HA makes it possible to individually tailor hearing devices to meet individual needs ( Banerjee & Garstecki, 2003 ). Multiple programs are available for diverse listening situations and offer advanced noise reduction strategies as well as reduction of acoustic feedback. CI have also benefited from this technology. However, studies indicate that sound quality still poses a problem. An Australian study, using a sample of 57 young adults with severe to profound hearing loss, revealed that the degree of contentment with the sound quality of HA was significantly related to the utilization of HA ( Cameron et al., 2008 ). Approximately 50% of the nonwearers were dissatisfied with the sound quality, whereas only 13.8% of regular hearing aid wearers felt the same. Bertoli et al. (2008) also found that noisy and disturbing sounds were the most frequently reported problems by adults. This finding indicates that despite advances in digital hearing aid technology and noise suppression algorithms, amplification may fail in a subgroup of HA users.

The option of a direct audio input in new digital HA/CI makes it possible to connect miniature FMs (called MLx receivers) to HA and CI via an audio shoe. Using general induction loops connected to the telecoil in HA and CI, FM technology (with use of MLx receivers) has become a more common practice. In addition to these two sound transmission systems, sound field amplification in which the entire classroom is amplified through the use of one, two, or four wall- or ceiling-mounted loudspeakers ( Crandell, Flexer, & Smaldino, 2005 ) is now offered to DHH students. According to Crandell et al. (2005) sound field amplification improves the learning environment for all students by enhancing the listening conditions. In addition, it can lead to improved student attention spans during teaching sessions ( Rosenberg et al., 1999 ). Because sound field systems improve the learning environment for all students, they may also lessen the embarrassment for DHH users.

Critical technological aspects also include cosmetic issues such as visibility and design. Invisible assistive hearing technologies appear to be preferred over visible ones, both in the case of personal amplifiers and assistive listening devices ( Cameron et al., 2008 ; Kent & Smith, 2006 ; Luckner & Muir, 2001 ; Preisler & Tvingstedt, 2005 ). In particular, older girls preferred less noticeable head-worn CI processors over those worn on the body ( Preisler & Tvingstedt, 2005 ). The potential spotlighting effect of body-worn FM receivers has been seen as a barrier; they were not stylish and singled out hearing-impaired students from their hearing classmates ( Luckner & Muir, 2001 ). Even miniature FM devices have been considered conspicuous and unattractive ( Kent & Smith, 2006 ).

The aim of this study was twofold. The main purpose was to explore predictors that could explain the differences in the dependent variable (i.e., students’ “uses of HA and CI”). The second purpose was to explore predictors that could impact students’ attitudes toward the following: (a) the sound quality of HA and CI, (b) the use of HA and CI, (c) the use of student-worn microphones, and (d) the use of teacher-worn microphones. Because the students’ attitudes toward the personal amplifiers were expected to be related to their use (or nonuse) of HA or CI, their attitudes toward the aides were investigated. The intention was to examine how different independent variables simultaneously affect attitudes toward hearing technology and the use of personal amplifiers among DHH children. Use of microphones was not explored, as this factor also depends on the teacher’s utilization of the equipment.

Three categories of independent variables including personal, technological, and environmental aspects were analyzed. Some variables were common to all of the hearing technologies, whereas others were specific to personal amplifiers or to assistive listening devices. The personal variables: (a) gender, (b) age, (c) hearing loss, and (d) students’ self-description were the common variables measured for the users of all hearing technologies. “Age of intervention with HA/CI” was only measured for the HA and CI users because not all students using microphones wore HA or CI. The personal variable “students’ view of the school” was explored for those with assistive listening devices but not to personal amplifiers because the latter are used during the entire day and are not limited to the school environment.

The technological variable that measured the attitudes toward “the sound quality” of the personal amplifiers were based on the type of equipment used (HA or CI). It was expected that the use of either an HA or CI could affect the perception of sound quality. The technological variables tested in terms of the assistive listening devices were the following: (a) technical problems with the microphones and (b) use of a sound field system. Often, technical problems with the microphones negatively impacted the attitudes toward microphones, whereas the use of a sound field system was assumed to be a positive influence, as this system can improve the listening environment for all students, not just for the DHH student ( Crandell et al., 2005 ). Unfortunately, technological aspects, such as the design and visibility of the hearing technologies, were not included in this study, even though several studies have shown that visible technology is more preferable over visible forms ( Cameron et al., 2008 ; Kent & Smith, 2006 ; Preisler & Tvingstedt, 2005 ).

The variable related to the environmental aspects was primarily students’ interaction with other DHH children, which was measured among the users of each hearing technology. The support experienced by DHH students from their families and friends is reportedly important ( Kent & Smith, 2006 ), but is not measured here. However, this study assumed that frequent contact with other DHH children could provide support leading to positive acceptance of one’s own hearing loss and bringing about positive attitudes toward the use of hearing technology.

In addition, the study investigated the factors influencing students’ reported use of HAs in terms of frequency. This analysis included two independent variables, attitudes toward HA/CI and sound quality in HA/CI, as well as the six previously listed independent variables related to attitudes toward HA/CI.

Subjects and Procedures

The participants in this study were children with mild to profound hearing loss between 10 and 16 years old. The participants had no intellectual impairments and were educated in inclusive schools. Most DHH students in Norway are in inclusive schools because of the “one school for all” principle. All students, including those with learning difficulties or exceptional abilities in certain areas, are supposed to meet challenges corresponding to their abilities; individual adaptation is regarded as essential targets to providing schooling of equal value, as specified by Norway’s educational authorities.

The participants were recruited from the Assistive Technology Centers (ATCs) and the National Resource Centers for hearing disabilities (NRCH). In each of Norway’s 19 counties there is one ATC that provides assistive technologies free of charge to people of all ages whose functioning in everyday life is considerably and persistently reduced. The associated costs are funded by social security. A different system operates in the case of HA and CI, as these provisions are the responsibility of hospitals ( Ravneberg, 2009 ). Six NRCHs take on the task of helping families, local schools, and municipal authorities to include DHH students in local schools. These centers offer supervision and guidance to individual children and their families as well as programs for municipalities, local schools, and child guidance services ( Simonsen, Kristoffersen, Hyde, & Hjulstad, 2009 ).

Twelve of the 19 ATCs contributed. Because five did not have the capacity to contribute four NRCHs replaced them. Two counties were omitted because they had taken part in a pilot project. In 2009, the ATCs and NRCHs were asked to list all DHH children born between 1992 and 1998 who had been supplied with assistive listening devices. The centers did not have the ability to identify the DHH students who attended special classes or those with concurrent intellectual disabilities. In all, 557 children were identified, which is fewer than the 790 children estimated to have hearing loss in those counties. Estimates suggest that 0.25% of all children and young people under 20 years old have hearing disabilities, with 10% of those suffering from profound hearing loss ( Kunnskapsdepartementet, 2001 ).

In spring 2009, invitations were sent to the 557 parents. The invitation gave details about the survey and the criteria for participation: (a) no intellectual impairment, (b) use of oral language, and (c) inclusive class enrollment. The subjects could respond with a paper questionnaire, with an Internet-based questionnaire, or in face-to-face interviews with the author. In addition, to information regarding the confidentiality of the research findings, the parents were informed that one child participant could win 130€ and that two children could win 65€. Of the 557 parents only 187 replied to the informational letters and permitted their children to participate. Ten parents responded that their child did not meet the participation criteria. The author contacted all 187 families, to determine the preferred participation method (i.e., paper questionnaire, Internet-based questionnaire, or face-to-face interview). The study also obtained additional information such as the type of hearing loss (e.g., unilateral deafness) and the age at which the hearing loss was ascertained.

Data were collected from May to December of 2009, and 153 children completed the questionnaire. The distribution of the responses was as follows: 46.8% by paper questionnaire survey, 34.4% by Internet-based questionnaire, and 18.8% through face-to-face interviews. Approximately 65% of the students who had completed the questionnaire online or in paper form stated that they had received help with filling out the form, whereas 35% responded independently. No significant differences (in terms of school grade or degree of hearing loss) were found between those who were assisted versus those who were unassisted. However, fewer students in the Internet group (51%) reported receiving help from their parents, whereas 68% of the students in the paper group were assisted by their parents. The chi-squared test for independence indicated significant associations ( x2 = 9.466, p =.009) between the groups. The majority of the students in the 5th and 6th grades responded either by paper or through face-to-face interviews, whereas the students in the 7th–10th grades more often answered via the Internet. The chi-squared test for independence indicated significant associations ( x2 = 10.955, p =.004) between the students in grades 5 and 6 compared with the students in the upper grades. In addition, slightly more students with severe hearing loss tended to be in the paper and face-to-face groups than found in the Internet group, however, the chi-squared test for independence revealed no significant differences ( x2 = 8.705, p =.069).

The final participation rate was low (28.1%). Information on gender, school grade, degree of hearing loss and family conditions was collected to identify potential biases. Table 1 shows the distributions for school grade, gender, and degree of hearing loss. Fewer students were in secondary schools than in primary schools, and slightly more boys than girls took part in the study. The majority of the students reported being able to hear speech from a distance of 1 m without using an HA, and none of the students selected the fourth category (cannot hear speech from a distance of 1 m while using an HA or CI). A smaller group of students characterized themselves as unable to always hear speech from a distance of 1 m while using an HA or CI, as seen in Table 1 . The number of CI users represented approximately 10% of all respondents.

A total of 76.2% of the students lived with both of their parents and 23.8% lived with one parent. According to Norwegian statistics, 75% of all children aged between 0 and 17 years old live in two-parent households ( Statistics Norway, 2010b ). Research on children with disabilities and family structures found that a slightly higher number of such children live with both parents compared with the general population ( Lundeby & Tøssebro, 2008 ). Of the students, 8.5% reported using a second oral language (in addition to Norwegian), and 6.5% reported using both sign language and spoken Norwegian. The remaining 85% communicated orally and in Norwegian only. First-generation immigrant children and Norwegian-born children with immigrant parents account for 9% of the population between the ages of 0 and 17 in the participating counties ( Statistics Norway, 2010a ).

The respondents represented 16 counties in Norway, including both rural and urban areas. The majority of the students (61.8%) were located in the eastern region and in the west coast of Norway. Others resided in southern Norway (14.5%), central Norway (13.9%), and northern Norway (9.8%). When compared with Norwegian statistics on the demographics of the general population, the findings were broadly similar, with the exception of northern Norway (slightly fewer students) and southern Norway (slightly more students).

All data were collected by the author. A pilot trial was first conducted with 2 hearing educators and 12 students (one student was in 2nd grade and the other students were in the 5th, 6th, or 7th grade). The paper questionnaire was expected to take approximately 30–60min for each participant to complete. The durations of the face-to-face interviews ranged from 30 to 90min, including short breaks for the youngest cohort of students. All face-to-face interviews took place in the home environment, with the exception of two sessions that were conducted at school.

Three types of sound transmission systems are provided to DHH students in Norway: (a) microphones combined with an inductive loop system, (b) microphones combined with an FM system, and (c) microphones connected to a sound field system. Each DHH student can be provided with one of the following: (a) a teacher microphone only, (b) a teacher microphone and a limited number of student microphones (1 microphone for every 3–7 classmates), or (c) teacher microphone and a high number of student microphones (1 microphone for every 1–2 classmates). During conversations classmates must press the microphone switch; handheld microphones are most commonly used, but desk microphones are used as well. Both teacher and student microphones must be regularly charged.

Table 2 presents the distribution of assistive technologies used by the children. The number of CI users was low (18). From 1988 to 1998, only 41 children received CI in Norway, in contrast, from 1999 to 2009, this figure reached 382 ( Bunne, 2009 ). The participants in this study were born between 1992 and 1998. One group of 43 students did not use any personal amplifiers; they all classified themselves as having mild to moderate hearing loss. In addition, unilateral deafness was reported by 20 students, and 16 had stopped using HA.

The distribution of the students (%, N = 153)

Note. CI, cochlear implants; HA, hearing aids.

Use of assistive hearing technology (%, N = 153)

The majority of the students were supplied with teacher microphones (cf. in Table 2 ). Most students used loudspeakers as the only sound transmitters, whereas the others used either inductive loops or FM systems both with and without loudspeakers. Approximately 31.3% used only FM or inductive loop systems. These numbers were in line with what the ATC had reported in telephone interviews regarding the systems delivered. Approximately 42% of the ATC reported delivering a sound field system only, an inductive loop, or an FM system only, whereas 23% of the centers could combine sound field amplification with an inductive loop or FM system. Because a relatively high number of centers (35%) had not started to distribute sound field systems either an inductive loop or FM system was the only system utilized. Most students were also supplied with student microphones; whereas the majority had one microphone per one or two classmates, others had one microphone per three to seven classmates (cf. in Table 2 ).

Table 3 presents the distribution of ages of intervention with HA or CI. Most children received their first HA between 3 and 5 years of age, but a relatively large percentage received their first HA after school age. Of these children 65% characterized themselves as having mild to moderate hearing loss, and 35% reported severe hearing loss. The modal age range for receiving CI was also between 3 and 5 years of age. The age for CI fitting has been reduced during the last 10 years, and the modal age range is now between 1 and 2 years old ( Bunne, 2009 ).

Age of onset with hearing aids (%, n = 114) and age of onset with cochlear implants (%, n = 18)

The survey questions were developed following a review of the relevant literature and information gathered from a pilot project. The dependent variables were the attitudes toward the following: (a) the sound quality of HA and CI, (b) use of HA and CI, (c) use of teacher-worn microphones, (d) use of student-worn microphones, and (e) students’ utilization of HA and CI. The independent variables were organized into the following areas: (a) student-related, (b) environmentally related, and (c) technically related.

Dependent Variables

Satisfaction with the sound quality of HA/CI . The sound quality of HA/CI was measured using the statement I like the sound in my HA/CI. The students responded using a 5-point Likert scale (totally agree, agree, neither disagree/nor agree, disagree, and totally disagree).

Satisfaction with HA/CI . Three attitudinal statements regarding the use of HA/CI were formulated. The statements were as follows: (a) I feel embarrassed when using HA/CI , (b) I am so used to my HA/CI that I do not mind what others think , and (c) I try to hide my HA/CI as much as possible. The rankings for the response options were the same as those for “satisfaction with the sound quality of HA/CI.” Item 2 was recorded with a positive rank. The three items were added to one variable (Cronbach’s α = .84).

Satisfaction with student microphones . The respondents experiences with student microphones were measured with five attitudinal statements: (a) I hear my classmates more clearly when using the microphones, (b) I feel embarrassed when my classmates use the microphones, (c) I like that my classmates use the microphones, (d) It is easy for my classmates to use the microphones correctly, and (e) I think that my classmates often joke around with the microphones. The response categories were the same as those for “satisfaction with the sound quality of HA/CI.” Principal component analysis (PCA) based on Kaiser’s criterion was implemented. The KMO did not reach the recommended value .60, but did reach .59. The Bartlett test result was significant. The PCA suggested two factors (eigenvalue = 2.39; 1.03; percent of variance = 47.91; 20.64). The first three items were suggested as one factor with a Cronbach’s α of .73, and represent the dependent variable analyzed here (items 1 and 3 were recorded as a positively ranked value). Items 4 and 5 were suggested as the second factor, but Cronbach’s α proved unsatisfactory. Thus, the items were treated as single independent variables that could affect “satisfaction with student microphones.”

Satisfaction with teacher microphones . The scales for measuring attitudes toward teacher microphones were similar to the first three statements used in the student microphones category, but the teachers were referred to instead of classmates. The response options were the same as those for “satisfaction with the sound quality of HA/CI.” A PCA suggested only one significant factor (eigenvalue = 2.07; percent of variance = 50.68). The Cronbach’s α of .73 was acceptable for the three statements.

Utilization of HA/CI . The utilization of HA and CI was assessed through two variables: How often do you use the HA or CI in the class ? and How often do you use the HA or CI during the school breaks ? The answer choices included never, seldom, sometimes, almost always and always. The two variables were added together and treated as one variable (Cronbach’s α = .84).

Independent Variables

Gender . 0 = males and 1 = females.

Age . Age was measured through school grade and transformed into a dichotomous variable (0 = secondary school, including grades 8–10, and 1 = primary school, including grades 5–7).

Hearing loss . The degree of hearing loss was recorded based on the student self-assessments. Table 1 presents the four response categories. The variable was transformed into a dichotomous variable. The first response category formed one group, and the second and third response categories formed the other group. No students selected the fourth response category.

Age of onset with HA/CI . Age of HA/CI fitting was split into six discrete categories: (a) 0–2 years, (b) 3–5 years, (c) 6–7 years, (d) 8–9 years, (e) 10–11 years, and (f) more than 12 years. The variable was transformed into a dichotomous variable (0 = more than 6 years and 1 = 0–5 years).

Self-description . The “Self-description Questionnaire” (SDQ II; Marsh, 1990), which was adapted and translated into Norwegian by Skaalvik in 1997, was used in this study ( Kvello, 2006 ). The scale consists of eight items with a Cronbach’s α of .81. An example item is I like myself as I am . The response alternatives were true, slightly true, slightly untrue and untrue.

Views of school . A scale developed by Rutter et al. (1979) was adapted and translated into Norwegian by Ogden (1995 ). It contains 10 items and represents three dimensions: (a) views of schools, (b) social well-being, and (c) further education ( Nordahl, 2000 ; Ogden, 1995 ). An example of an item on this scale is I usually like to go to school , which measured on a Likert scale with five response alternatives (totally disagree, disagree, neither disagree/nor agree, agree, totally agree). Only one dimension was included in the survey (views of school). The Cronbach’s α of .56 on view of school suggests unsatisfactory reliability and is also lower than the .63 score produced in Nordahl’s study. Nevertheless, the dimension was incorporated into the analysis.

Quality of teaching . This variable contains 4 items and has a Cronbach’s α of .71, it was adopted from the Quality of School Life scale developed by Karatzias, Power, and Swanson ( Våge, 2007 ). The scale consists of 14 dimensions, but only the Quality of Teaching dimension was included. An example item is I like the way I am being taught . The response categories were similar to those used for “the views of school” variable.

Interaction with other DHH children . Interaction with other DHH children was measured with two variables. The first was How often have you participated in student courses with other DHH children ? This variable had response alternatives of never, once, 2–3 times , and 4–5 times . This variable was transformed into a dichotomous variable (never/once = 0 more than 2 = 1), and labeled “ participated in courses.” The second variable asked the respondents How often are you together with other DHH children ? The response options were seldom or never, once a year, several times a year, several times a month, several times a week , and daily . The variable was renamed “contact with DHH children.”

Technical problems with teacher microphones . Tech nical problems were measured using the statement There is often something wrong with the teacher microphone. The response categories were arranged on a 5-point Likert scale (totally agree, agree, neither disagree/nor agree, disagree, and totally disagree).

Technical problems with student microphones . These problems were assessed using the teacher microphone questions, but “student microphones” was used in place of “teacher microphone.”

Sound field system . 0 = no sound field system, 1 = sound field system.

Use of HA or CI . 0 = HA, 1 = CI.

All of the statistical analyses were performed using the Statistical Package for Social Sciences (SPSS) version 18.0 for Windows (SPSS Inc., Chicago, IL, USA, 2003). The statistical significance level was set at 0.05. Principal component analysis and reliability testing were conducted to evaluate data reduction for the two dependent variables (satisfaction with teacher and student microphones) and the composed independent variables. Cronbach’s α was computed to estimate the internal consistency of all instruments used.

Descriptive statistics, including means and standard deviations, were calculated for the continuous variables. Hierarchical multiple regression analyses enabled the study to explore the variables affecting all of the dependent variables (i.e., satisfaction with HA/CI, satisfaction with the sound quality of HA, satisfaction with teacher microphones, satisfaction with student microphones, and utilization of HA). Prior to the multiple regressions analyses, bivariate regression analyses were performed and only the predictors with significant effects on the dependent variables were included in the multiple regression analyses. Missing data were treated using pairwise exclusions.

Data Screening and Collinearity Diagnostics

Data screening revealed negatively skewed distributions on all of the dependent variables, but this study decided not to transform the variables. The use of collinearity diagnostics in the multiple regression analyses indicated no collinearity on “satisfaction with HA/CI” (tolerance: 0.73–0.99; variance inflation factor (VIF): 1.00–1.36). The Durbin–Watson test results fell within the boundaries of acceptance (Durbin–Watson = 1.69). Similarly, an interpretation of residuals was found to be acceptable (Cook’s distance <1). The Durbin–Watson test, collinearity diagnostics, and interpretation for the residuals on “satisfaction with sound quality of HA/CI” also fell within acceptable boundaries (Durbin–Watson test: 2.12; tolerance: 0.60–0.86; VIF: 1.09–1.64; Cook’s distance <1). The following scores on the variable “satisfaction with teacher microphones” were obtained: Durbin–Watson test: 2.21; tolerance: 0.77–0.99; VIF: 1.00–1.29; Cook’s distance <1. The scores for the variable “satisfaction with student microphones” were as follows: Durbin–Watson test: 2.19; tolerance: 0.72–0.97; VIF: 1.02–1.38; Cook’s distance <1. The figures also lay within the boundaries of acceptance for the variable “utilization of HA” (Durbin–Watson test: 1.82; tolerance: 0.75–0.92; VIF: 1.10–1.32; Cook’s distance <1).

The independent variables were related to personal, environmental, and technological aspects. Some of the personal variables, such as “age of onset with HA/CI” were evaluated only in terms of satisfaction with HA/CI. Similarly “views of schools” were investigated in terms of satisfaction with microphones.

Hierarchal multiple regressions were used to assess the effectiveness of the measures in predicting levels of satisfaction with assistive hearing technologies. Table 4 analyzes the respondents’ satisfaction with the hearing technologies, and Table 5 analyzes utilization of HA. The predictors with insignificant effects on the dependent variables in a preliminary bivariate regression analysis were not included in the multiple regression analyses; in these cases, the cells appear blank, as seen in the tables. Differences emerged with regard to the predictors that had significant effects on particular dependent variables. Finally, the analysis of “utilization of HA” is presented.

Multiple regression analysis predicting attitudes to assistive hearing technologies

Note . B, unstandardized beta coefficients; CI, cochlear implants; DHH, deaf and hard-of-hearing; HA, hearing aids; SE, standard error. Predictors lacking statistical significance in the bivariate analyses on dependent variables are not given.

* p < .05, ** p < .01.

Multiple regression analysis predicting utilization of hearing aids (HA)

Note. *p < .01, **p < .01.

Satisfaction With the Sound Quality of HA/CI

The independent variables assumed to affect satisfaction with the sound quality were gender, age, use of HA or CI, hearing loss, age of onset with HA/CI, self-description, contact with DHH children, and participation in courses. In the bivariate regression analyses age of onset with an HA/CI, hearing loss, use of HA or CI, contact with DHH children, and participation in courses appeared to be significant predictors and were implemented in the multiple regression analysis.

With regard to the multiple regression control model for the other variables as seen in column 1 of Table 4 , the significant predictors were use of HA or CI (β =.185, p < .05), hearing loss ( β = .201, p < .05), and age of onset with an HA/CI ( β =.290, p < .01). The students who used a CI tended to be more satisfied with the sound quality and contributed to distributions of 3%. In addition, the students with severe hearing loss or who started using HA before school age were more likely to be satisfied with the sound quality than the students with mild to moderate hearing loss or who were fitted after school age. This unique distribution corresponded to 3% and 7%, respectively, of the total adjusted R 2 . “Participation in courses” and “contact with other DHH children” was insignificant in the multiple regression analysis.

Almost all 18 students wearing CI were satisfied with the sound quality, except for one who stated “both” because of a new CI in the other ear. Figure 1 illustrates the students’ respective satisfaction levels with the sound quality of CI and HA. A small subset of the students who used HA did not agree with the statement I like the sound in HA , whereas a relatively large group stated “both/or” and the majority agreed. An independent sample t test was conducted and showed significant differences in the sound quality scores of the users of CI ( M = 4.72, SD = 0.57) and HA ( M = 3.64, SD = 1.11, t (104) = −4.01, p = .01). High scores indicate positive attitudes.

The clustered bar chart of the distribution of I like the sound in my HA/CI between HA users and CI users ( n =112). Frequencies = n .

Satisfaction With HA/CI

The independent variables measured in the bivariate regression analyses for “satisfaction with the sound quality of HA/CI” were also used in the bivariate regression analyses for “satisfaction with HA/CI.” In addition, “satisfaction with the sound quality of HA/CI” was assumed to explain the differences in satisfaction HA/CI. The bivariate analyses showed that gender, hearing loss, age of onset with HA/CI, self-description, and satisfaction with the sound quality of HA/CI were all significant. These factors were all included in the multiple regression analysis.

Column 2 of Table 4 shows that three predictors hearing loss ( β = .231, p < .05), gender (β = .278, p < 0.001), and self-descriptions ( β = .227, p < .05) were found to be significant when each factor was controlled for in the analysis. The students with more severe hearing loss appeared to feel more positively towards HA/CI than the students with mild to moderate hearing loss, and contributed to 4% of the adjusted R 2 . The boys also tended to be more satisfied with HA/CI than the girls, and the distribution for gender was 7% of the total adjusted R 2 . In addition, the students with positive self-descriptions seemed more satisfied than the students with negative self-descriptions, and comprised 4% of the adjusted R 2 . No associations were found between this dependent variable and the degree of “satisfaction with sound quality of HA/CI” or “age of onset with HA.”

Satisfaction With Teacher Microphones

The regression analyses using “satisfaction with teacher microphones” as a dependent variable included the same independent variables as the analyses using “satisfaction with HA/CI” as a dependent variable, except that “age of onset with HA/CI” was not included. In addition, the analysis of “satisfaction with teacher microphones” included the independent variables of “views of school,” “quality of teaching,” “technical problems with teacher microphones,” and “use of a sound field system.” The preliminary bivariate regression analyses showed that gender, self-description, views of school, quality of teaching, and technical problems with teacher microphones were significant predictors. Thus, these factors were incorporated into the multiple regression analysis.

For the multiple regression analysis, three variables were significant, as shown in column 3 of Table 4 . These variables were gender (β = .212, p < .05), views of school ( β = .202, p < .05), and technical problems with the microphones ( β = .169, p < .05). The boys tended to be more satisfied with teacher microphones than the girls. The distribution of gender was 4% of the total adjusted R 2 . The students who had more positive views of school and who had experienced few problems with the equipment indicated greater satisfaction with teacher microphones. These two variables contributed to a unique explanation on 3.5% and 3%, respectively, of the total adjusted R 2 . The two other variables “self-description” and “quality of teaching” became insignificant when the study controlled for the other predictors.

Satisfaction With Student Microphones

The variables assumed to impact the students’ satisfaction with student microphones were parallel to those affecting teacher microphones satisfaction. In addition, the independent variable “I think that classmates often joke around with the microphones” was measured. The predictors with significant effects, as shown in the bivariate regression analyses, included gender, self-description, views of school, quality of teaching, errors with the student microphones, and “classmates often joke.” Hence, these predictors were included in the multiple regression analysis.

Column 4 of Table 4 shows the multiple regression analysis for “satisfaction with student microphones.” Significant predictors were gender, views of school, and technical problems with the microphones. In terms of teacher microphone and HA/CI, the boys ( β = 196, p < .05) appeared to feel more positively toward student microphones than the girls and comprised 3.3% of the variance in the dependent variable. Similar to satisfaction with teacher microphones “views of school” ( β = .305, p < .001) was a central predictor that corresponded to approximately 8% of the adjusted R 2 . Technical problems with the student microphones ( β = .246, p < .001) also impacted the students’ satisfaction. Fewer technical problems with the microphones led to higher satisfaction with the student microphones and explained 5.5% of the adjusted R 2 . When these predictors were controlled for the “self-description,” “classmates often joke around . . .” and “quality of teaching” variables became insignificant.

Utilization of HA/CI

Almost all of the students with severe hearing loss and the CI users constantly wore their personal amplifiers in school; consequently, only the students with mild to moderate hearing loss were evaluated with regard to utilization of HA. The mild to moderate hearing loss group using HA comprised 46 students. Approximately 44% of them irregularly or never wore HA during lessons and breaks, whereas 56% almost always or always used them. The main predictors anticipated to affect utilization of HA were satisfaction with HA and satisfaction with the sound quality of the HA. In addition, the independent variables of gender, age, age of onset with HA, self-description, contact with other DHH children, and participation in courses were presumed to have direct effects. Although the preliminary bivariate analyses showed that the girls used HA more regularly than the boys, this difference was not significant. Aside from the students’ satisfaction with HA and their sound quality, only the variable of “self-description” appeared significant in the bivariate regression analyses.

Table 5 shows the multivariate linear regression model, which predicts the outcomes of the dependent variable. All of the variables appeared significant (“satisfaction with wearing HA,” β = .404, p < .01, “satisfaction with the sound quality of HA,” β = .445, p < .001, and “self-description,” β = −.315, p < .05). The students satisfied with wearing HA and with the sound quality seemed more willing to use HA constantly. The prevalence of the two variables was 14% and 17%, respectively, of the adjusted R 2 . The analyses showed that self-description had the opposite effect compared with the students’ satisfaction with HA, low self-description led to greater use of HA whereas high self-description promoted greater satisfaction with HA. This variable explained approximately 7% of the total adjusted R 2 .

The present investigation of DHH children’s opinions of hearing technology aimed to explore the factors influencing students’ satisfaction with hearing technologies and utilization of HA. On the basis of findings from other studies, it was assumed that personal, environmental, and technological factors could explain the variations in the dependent variables.

The findings here indicated that all students who wore CI were satisfied with the sound quality of their CI. The students with HA who had severe hearing loss or who were fitted with an HA/CI prior to school age tended to be more satisfied with the sound quality of the HA than the students who had mild to moderate hearing loss or who were fitted after school age. According to several studies, students with CI have integrated them as natural parts of their lives ( Preisler & Tvingstedt, 2005 ; Wheeler et al., 2007 ). In addition, students with severe hearing loss may be strongly dependent on their HA, which can explain why both groups tended to be more satisfied with the sound quality. The reasons explaining why the students who are introduced to HA later on became unsatisfied may be connected to the information provided by their parents; for many of the students the hearing loss was first discovered after school age. Hearing loss diagnosed later can have particular implications; sound signals that do not reach the brain will be forgotten over time and can only be reproduced through conscious effort. Furthermore, within the first year, infants experience a reduced ability to perceive differences among phonetic contrasts that are not used or heard in their linguistic environment ( Bisgaard, 2008 ; Olaussen, 2010 ). Consequently, children who are diagnosed late may not adapt as easily to the sound provided in the HA compared with children who are diagnosed early. Although newborns can now be screened for hearing loss, universal newborn screening protocols do not target hearing loss in the minimal to mild ranges ( Johnson et al., 2005 ), and children with minimal to mild degrees of hearing loss are still not likely to be identified until approximately 5 to 6 years of age ( Tharpe, 2007 ).

The students’ satisfaction with the HA/CI appeared to be related to hearing loss, gender, and psychosocial dimensions. Having severe hearing loss seemed to make students more content with their HA/CI, as other studies have revealed ( Bertoli et al., 2009 ; Clarke & Horvath, 1979 ; Smeeth et al., 2002 ; Vesterager & Parving, 1995 ). In addition, the boys tended to be more positively oriented toward personal amplifiers than the girls. These results contradict those of other studies, where females are reported to accept their hearing loss and to use HA to a greater extent than males ( Bertoli et al., 2009 ; Coniavitis-Gellerstedt, 2006 ; Smeeth et al., 2002 ). However, the results of this study are in line with Solheim’s (2011) findings, which found more positive attitudes toward HA among elderly males than among elderly females. Nevertheless, the male effect here may be specific to the young group of children. Furthermore, consistent with other studies that have pointed to psychosocial dimensions as central explanations for attitudes and the use or nonuse of hearing technology, high levels of positive self-description was positively related to the students’ satisfaction with their HA/CI ( Cienkowski & Pimentel, 2001 ; Garstecki, 1996 ; A. Helvik, Jacobsen, & Hallberg, 2006 ; Kent & Smith, 2006 ).

The boys also tended to be more satisfied with both teacher and student microphones than the girls. In addition, the psychosocial dimension measuring the students’ “views of school” was related to satisfaction with the microphones. Interestingly, the students with positive attitudes toward the school were more content with the microphones than the students with negative views. Although hearing loss was related to satisfaction with HA/CI, no differences were found between the students with mild to moderate hearing loss and the students with severe hearing loss in terms of the students’ satisfaction with the microphones. Both teacher and student microphones seemed to be valued by both groups of students. Self-description was not related to satisfaction with the microphones or the “classmates often joke around with the microphones” variable when the other variables were controlled for, even though it would be reasonable to presume that the latter one would have a negative effect on satisfaction with the student microphones. The technical equipment such as sound field systems was thought to promote satisfaction with the assistive listening devices because it may feel less embarrassing for DHH students. However, it did not appear to be associated with the students’ satisfaction with the microphones. Use of the microphones is limited to classrooms, where the students’ hearing loss is probably well known, whereas personal amplifiers are commonly used in daily life, including settings where the students’ hearing loss is unknown; in such situations, the HA/CI may be commented upon by the students’ peers. Kent and Smith (2005) describe two different strategies for handling comments; by ignoring the comments (which would have a constructive effect) or by perceiving the situation as an unwanted and stigmatizing teasing episode. Inherent in stigmatization is a perceived risk of being identified as abnormal, which may impact children’s self-descriptions, as the current study demonstrates; low self-descriptions impacted the students’ satisfaction with the personal amplifiers, but not toward the microphones. Consequently, the type of environment in which the hearing technology is used seems to be essential. However, the assumption that frequent contact with other DHH children could be supportive and lead to positive attitudes toward hearing technologies was not associated with the students’ satisfaction. Accordingly, because the students seemed to appreciate the microphones frequent technical problems with the microphones contributed negatively to the students’ satisfaction. In total, 30% of the respondents stated that there were often technical problems with the teacher microphones, and 20% stated the same for student microphones. The frequency of technical problems is challenging and should be further explored.

This study revealed that only the students with mild to moderate hearing loss were infrequent HA wearers. Consistent with the findings of other studies, all students with CI used them constantly, and nearly all students with severe hearing loss used their HA regularly at school ( Clarke & Horvath, 1979 ; Vesterager & Parving, 1995 ). The students with severe hearing loss clearly have less choice concerning the use of their HA. The students in the group with mild to moderate hearing loss who were comfortable with wearing HA (in the sense that they felt less embarrassed or cared less about what other people thought about their HA) were more likely to use them. According to Polgar (2010) , individuals who see technology as a visible sign of disability reinforce the stigma associated with disability. Consequently, they avoid using the technology, as these results indicate.

The students satisfied with the sound quality also tended to be consistent wearers of HA. This study revealed that several HA users were more dissatisfied with the sound quality than the CI users, nearly all of whom were satisfied with the sound quality. Cameron et al. (2008) reported similar findings and found that approximately 16% of 57 young adults were dissatisfied with the sound quality of their HA, 30% were unsure, and 53% were satisfied. Others have also pointed to sound quality as the most frequently reported problem by adults ( Bertoli et al., 2009 ). This study seems to support Bertoli et al., who claim that, despite the advances in digital hearing aid technology and noise suppression algorithms, amplification may fail in a subgroup of HA users. In Heeney’s (2007) study, the young participants proposed two recommendations that could improve their satisfaction with personal amplification systems; better access to information regarding hearing aid options and better sound quality in HA. In line with this finding, 43% of the students in the pilot study reported being unfamiliar with their HA options, including the number of applications and what they represented ( Rekkedal, 2007 ). In addition, Heeney reported that several of the adolescents had negative attitudes toward the hearing service providers, with only 64.9% of the respondents feeling that their audiologists cared about their hearing. These issues were not touched upon in this study, but because the sound quality posed a problem for DHH children and impacted their uses of HA, this issue would also benefit from further consideration and investigation.

Surprisingly, although the boys were more positive toward the use of HA, this perception did not seem to have any bearing on their use of HA. Instead, the girls appeared to use HA more regularly, even though they did not appreciate using them. Consequently, the effect resulting from the boys’ satisfaction with the use of HA became unimportant. Although, positive attitudes toward HA influence their use, the psychosocial aspect of self-description had the opposite impact, whereas positive self-descriptions indicated positive attitudes toward HA, a negative self-description predicted constant use in this case. The cause for this relationship is unclear but may be related to gender. The girls generally appeared to have significantly lower self-descriptions that the boys, who rated their self-descriptions higher. Other studies concerning self-esteem and self-descriptions among adolescents describe parallel differences in gender; girls generally rank themselves lower than boys ( Gadbois & Bowker, 2007 ; Moksnes, Moljord, Espnes, & Byrne, 2010 ). Because the girls in this group tended to use HA more frequently, a lower self-description may be related to constant use; thus, gender can be an underlying factor in understanding DHH students’ uses of HA. The group also differed from the total sample regarding independent variables with impacts on “satisfaction with HA”; gender did not predict any significant differences, whereas “age of onset with HA” appeared to be significantly related in this group. In addition, the number of respondents was low and therefore more difficult to analyze.

A relatively large portion of the students (i.e., approximately 38%) received their first HA after starting their compulsory education. Still, the findings here did not support the argument that having students fitted early on with HA directly influenced their utilizations of HA: rather to a certain degree, the results supported the findings of Vesterager and Parving (1995 ), who did not find differences between students fitted early and those fitted late, which may disprove Gillies’s (1997) findings that implicate age of intervention as a main factor. However, age of intervention seemed to have an indirect effect on the utilization of HA in this group; the students who received later interventions with HA tended to feel more negatively about the sound quality of their HA and less satisfied with the HA. This finding indicates that children fitted later with HA may be a group at risk that requires follow-up by professionals.

Students with mild hearing loss are reportedly more often ignored by teachers because they are believed to function more easily and have less need for support services than students with severe hearing loss ( Convertino, Marschark, Sapere, Sarchet, & Zupan, 2009 ). However, poor listening conditions in classrooms can create considerable difficulties for students with mild hearing as well ( Antia, Jones, Reed, & Kreimeyer, 2009 ). In addition, previous findings indicate that these students’ academic levels lag behind their hearing peers’ academic performance ( Daud, Noor, Abd Rahman, Sidek, & Mohamad, 2010 ). Accordingly, professionals should be attentive to this group, as these students use HA more irregularly at school, which may further reduce their abilities to understand classroom communications.

Several studies have pointed to children’s ages as an explanation for the differences in students’ views of and willingness to use HA ( Clarke & Horvath, 1979 ; Coniavitis-Gellerstedt, 2006 ; Wennergren, 2008 ; Winn, 2006 ). The findings here did not show any differences between students in primary and secondary school on students’ satisfaction with assistive hearing technologies or the use of HA. Some studies have shown that the main decrease in use of HA occurs after the transition from elementary to high school ( Gellerstedt, 2006 ; Winn, 2006 ). In this study, no students at the high school level participated, which may explain the absence of similar findings.

Because the study had a low response rate, care should be exercised in the generalizing these findings to the total population of hearing-impaired children. There was a particular focus on the following set of dimensions: (a) personal factors, such as age, and self-description; and (b) technical factors, such as type of equipments, sound quality, and technical problems. These may offer likely explanations for the variances seen in the respondents’ attitudes towards the hearing technologies. If the study had included data on specific audiograms, design, visibility, types of HA and microphones, fuller explanations could have been obtained. Because the effects and causes of the students’ utilizations of HA were difficult to construe care should be exercised in the generalization of these findings. Access to the audiograms may perhaps have improved the explanation of the predictors of students’ utilizations of HA.

No conflicts of interest were reported.

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Meeting the educational needs of children with hearing loss

Karissa l leclair.

a Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, United States of America (USA).

James E Saunders

b Department of Otolaryngology, Dartmouth-Hitchcock Medical Center, 1 Medical Center Drive, Lebanon, New Hampshire 03756, USA.

Paediatric hearing loss is a growing public health issue that is currently a significant barrier to achieving sustainable development goal 4 (SDG 4), that is, quality education for all. 1 When children with hearing loss do not receive treatment, they might have difficulty accessing mainstream schooling and therefore obtain worse educational outcomes. The severity of these implications is correlated with level of hearing loss and earlier age of onset. 2 , 3 Children with any degree of hearing impairment have been shown to exhibit poor language development, leading to lower literacy rates, diminished social skills and impaired executive function capacity. 3 Different severities of hearing loss must be considered, as a child’s ability to access schooling and participate in integrated education is highly dependent on level of hearing loss. 4 A child’s educational ability can be affected at a milder severity of hearing loss than what was considered as disabling. Consequently, the global burden of educationally disabling hearing loss is larger than previously estimated by the World Health Organization (WHO). 5

Mild hearing loss, that is, a hearing level threshold between 26–40 decibel (dB) in the better ear, affects almost 50 million children worldwide, yet is frequently overlooked and undertreated. 6 A 2016 review concluded that children with mild hearing loss, overall, tend to have compromised speech recognition and poorer language skills. 7 Therefore, these children are over 2.5 times more likely to have academic difficulties and they more commonly experience grade retention. One study indicated that 37% (24/66) of children in a cohort with mild hearing loss had failed at least one grade. 7 , 8 With respect to children affected by moderate hearing loss (41–60 dB), educational impairments mirror the deficits of those with mild losses, yet are more common and impactful. A study from France reported nearly half of children with moderate hearing loss had experienced one or more years of grade retention. 8 Standardized academic test scores for children at all levels of hearing impairment are significantly lower than those of children with normal hearing, and notably demonstrate a strong correlation with the severity of hearing loss. 2

Academic achievement for children with severe (61–80 dB) to profound (> 80 dB) hearing loss is significantly hindered relative to peers, with one third of children functionally illiterate upon graduation from secondary school. 9 Furthermore, severe to profound hearing loss has been shown to have a significant effect on a child’s ability to participate in mainstream education. A study in the United States of America showed that only 22% (1536/6980) of children with severe hearing loss and 10% (1517/15 174) of those with profound hearing loss participated in integrated mainstream education for more than half of their school day. 4 These data identify a crucial objective for improvement, as those with hearing loss who are unable to access mainstream education face impaired academic and language outcomes. 2

Children with unilateral hearing loss (that is, who are hearing impaired in one ear only) should also be included, as they may experience similar educational barriers as children with mild deficits. Unilateral hearing loss causes difficulty in localization of sound and impairs the ability to hear in noisy settings such as a classroom. Additionally, this deficit has been associated with lower oral language scores when compared to normal-hearing counterparts. 7

The global prevalence of hearing loss must be discussed to better understand the burden of this condition. Research has traditionally focused on characterizing the prevalence of disabling hearing loss (> 30 dB) – identifying 34 million children worldwide affected at this threshold or greater. 5 However, even mild hearing loss has potential for detrimental effects on education. 7 , 8 Therefore, educationally disabling hearing loss should include all thresholds of mild hearing loss, significantly increasing the number of children characterized as at risk. To calculate updated numbers of children affected at each level of disability, global prevalence rates were applied to the most recent 2018 population data. 6 These estimates identify 61 million children from birth to 14 years of age, globally, who have some degree of hearing impairment with potential effect on their educational outcomes. This number nearly doubles the previous estimate of children whose hearing loss met thresholds traditionally considered disabling. 5 , 6

Latest available global prevalence estimates of childhood hearing loss range show significant regional variability. Low- and middle-income countries in geographical areas, such as south Asia, are disparately affected: 82.5% (95% confidence interval, CI: 45–151.4) for mild hearing loss; 14.3% (95% CI: 7.4–29.7) for moderate hearing loss; 0.7% (95% CI: 0.3–1.4) for severe hearing loss; and 0.2% (95% CI: 0.1–0.4) for profound hearing loss, while high-income countries contribute only a small fraction of the global burden. In these countries, the prevalence for mild hearing loss is 17% (95% CI: 12.4–25); for moderate hearing loss is 2.7% (95% CI: 2.0–4.0); for severe hearing loss is 0.1% (95% CI: 0.1–0.2); and for profound hearing loss is 0.0% (95% CI: 0.0–0.1). 6 Rates of disabling hearing loss have been shown to increase exponentially as gross national income decreases, with a nearly fivefold prevalence in some low- and middle-income regions as compared to high-income nations. 6 Following this same trend, access to hearing health care is correlated with national income levels. Low- and middle-income countries consistently report insufficient numbers of otolaryngologists, audiologists and speech therapists per capita. 10 While WHO’s minimum standard recommends 40 otolaryngologists per 1 million people, more than two thirds of low-income countries do not even have one otolaryngologist per million people. 10 With respect to device availability, global production of hearing aids is estimated to meet less than 10% of global need and less than 3% of need in low-income countries. 5

While the current global state of paediatric hearing loss may appear dismal, promising data indicates that 60% of this hearing loss is preventable. These common preventable causes include infectious causes, birth complications, noise exposure and the use of ototoxic medications in pregnant women and children. 5 Notably, WHO estimates that preventable causes are more likely to be the etiology of hearing loss in low- and middle-income countries (75% of all hearing loss) as compared to high-income countries (49%). 5 This disparity has been attributed to regional trends such as higher infection rates, overuse of ototoxic antibiotics, and lack of adequate maternal and fetal care in low- and middle-income countries. 5 In addition to the opportunity for primary prevention, evidence demonstrates that early detection and treatment can protect against language and educational consequences. 3 Even children with profound hearing loss exhibited speech and language levels equal to their hearing peers after receiving early diagnosis and a treatment regime of hearing amplification, auditory and verbal therapy, and cochlear implantation by 18 months of age. 11 The specific intervention must be tailored to the level of hearing loss and in-country resources, but promisingly, several effective options including hearing aids, speech rehabilitation, cochlear implantation and deaf education are available. 5 Newborn hearing screening is a crucial aspect of this process, as early detection leads to early intervention, a vital predictor of future language and educational outcomes. 3

To assess global progress towards achieving quality education for all, evidence of paediatric hearing loss being a barrier to this goal should be considered. SDG 4 designates universal education as one of our highest global priorities, specifically aiming to ensure equal access to all levels of education for the vulnerable, including persons with disabilities. 1 To achieve this quality education mandate, we must first address the educational repercussions of this common disability through appropriate efforts in hearing loss prevention, identification and treatment.

Particularly within low- and middle-income countries, increased preventative efforts will be the most cost–effective and high-yield strategy to combat educationally disabling hearing loss. Reduction of paediatric hearing loss can be accomplished through expansion of basic low-cost health provisions, such as measles, mumps and rubella vaccines to prevent rubella-associated hearing loss. Another option is to provide easily accessible treatment for otitis media, to address chronic ear infections as a common etiology. Awareness raising will be the single most important aspect of addressing paediatric hearing loss on a global scale. Patients and health providers must be informed on topics such as the ototoxic effects of unregulated antibiotic use, safe and hygienic practices for labour and delivery, and potentially-dangerous exposures for mothers during pregnancy. However, education should also include expanding awareness of the widespread burden of paediatric hearing loss, highlighting common early presentations of this disease and emphasizing the potential for long-term effects if left untreated. Such awareness will be crucial in fighting the stigma associated to this disability, both encouraging schools to provide resources for inclusion of affected children, as well as enabling parents to recognize and seek treatment for children at an early age.

Beyond prevention, newborn screening for early identification of hearing loss should be expanded and standardized. However, such efforts will require sufficient availability of otolaryngology and audiology resources to provide treatment following detection. This objective will require hearing health-care investment and expansion in low- and middle-income countries, where children currently have high rates of hearing loss, yet have little or no access to rehabilitation services. Although this objective would be a large-scale investment, the long-term outcomes of hearing loss detection and intervention programmes have been shown to be cost–effective because they mitigate educational deficits and lost productivity. 5 Children with mild hearing loss must also be included when considering the scope of such investment, as even mild deficits are frequently detrimental to a child’s language ability and educational access. If the global community hopes to achieve SDG 4, a concrete objective is to first address this treatable disability.

Competing interests:

None declared.

Students with hearing loss get a raw deal: a South African case study

Researcher , Cape Peninsula University of Technology

Professor, Stellenbosch University

Disclosure statement

Dr Diane Bell is affiliated with the Carel du Toit Trust, an NPO in Cape Town.

Estelle Swart does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

Cape Peninsula University of Technology and Stellenbosch University provide funding as partners of The Conversation AFRICA.

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Hearing loss is the fourth highest cause of disability globally. The World Health Organisation estimates that there are currently 466 million people with a disabling hearing loss. Two thirds live in low and middle income countries.

In the UK , 2.33% of students with a disability disclosed being deaf (using sign language) or hard of hearing. In Australia , students with a hearing loss comprise of about 10% of the cohort of students with disabilities.

Studies show that up to 75% of students with a hearing loss who do manage to enter higher education don’t graduate . Those who do are often excluded from entering professions.

These global trends are also relevant in South Africa where universities are accepting and registering students with mild, moderate and severe hearing loss, but are failing to provide them with the necessary academic support, or accessible and inclusive curricula.

Statistics about the numbers of university students who have disclosed disabilities, and more specifically hearing loss, aren’t readily available. But, what we do know is that students who are hard of hearing are being granted access to university increasingly, yet they remain under supported. This often results in poor academic outcomes.

Generally, there is a lack of research about students using hearing technology and those who use spoken language. Not much is known about their educational experiences, the teaching and learning support provided to them and their teaching and learning needs. Very little is known about how they cope with academic live.

We did research to explore the teaching and learning experiences of students with hearing impairments at university and the daily barriers they face. We also provided suggestions on how to improve teaching and learning, and how to promote curricula transformation.

The findings

Our findings showed that teaching practices at the university we used for the case study were not inclusive and that curricula were largely inflexible. We selected this university for our study because it had a relatively large number of students with hearing impairments. Although this research explored the experiences of students with hearing impairments at one university, these findings can be generalised across higher education institutions throughout South Africa.

Our study found that reasonable academic adjustments, such as strategies to minimise or remove the effects of a disability to enable learning, were extremely limited. This means that these students didn’t have access and equal opportunity to participate in all the university’s activities.

Secondly, the support services offered at the university to students with hearing impairments were inadequate. Often, the students didn’t know what support was available to them. And even where it was in place the support didn’t meet the unique needs of the students.

The third finding showed that all hard of hearing students at the university experienced a significant number of learning barriers. These included:

Difficulty following class discussions due to high levels of background noise and poor acoustics, especially in large venues.

Inaccessible teaching practices, such as when the lecturer talks while turning his/ her back to write on the white board or chalkboard or showing videos without subtitles.

Inability to hear or lip-read, especially when lecturers switched between two languages or rapidly changed topics without warning.

Poor lighting when using a data/ video projector because students with hearing impairments weren’t able to lip-read.

Some attempts had been made by the university to be more inclusive. But the students still felt inadequately supported in terms of their unique learning and communication needs.

Moreover, students with disabilities in higher education remain marginalised and insufficiently supported. This interferes with their human rights despite progressive legislative framework in South Africa and the noble commitments to right the wrongs of the past.

Recommendations

The participants in the study made a number of recommendations . These included:

University lecturers must receive training around the principles of universal design for learning and knowledge in relation to hearing loss, and how best to support students with a hearing disabilities.

Support should be tailored to address the individualised need of students.

Large teaching venues should be fitted with good quality audio equipment such as microphones.

Induction loop systems should be installed in larger teaching venues. These systems transmit an audio signal directly into hearing aids/ speech processors through a magnetic field. This reduces background noise, competing sounds and other acoustic distortions that reduce clarity of sound.

A compulsory module on diversity, disability and inclusion should be offered in every course at a first year level.

Unless there is a cultural and attitudinal change at universities, and unless strategies are put into place to support hard of hearing students, they will continue to experience significant barriers to learning. These will have a negative effect on not only their educational experience but also their academic success.

A call to action is being made for university administrators, disability support units and lecturers to provide adequate and appropriate support to ensure equitable access to learning and thus a fair chance of academic success.

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• Hearing loss
• Hearing aids
• Inclusive education
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Challenges faced by Hearing Impaired pupils in learning: A case study of King George VI Memorial School

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The study analysed the challenges faced by schools when imparting prevocational skills to learners with hearing. The mixed methods design was used. Data was collected from a representative sample of 10 teachers and 30 learners with hearing impairments using questerviews and focus group discussions respectively. The results showed that The major challenges faced included poor communication and language skills, lack of proficiency in sign language, shortage of resource materials to use and the negative attitudes by staff members. For improvement it was suggested that teachers and students all need to learn sign language as it is now one of the official languages in Zimbabwe. There is also need for specialists teachers to act as sign language interpreters when the need arises. In addition students need to be provided with hearing aids to enhance their hearing and improve their participation in class. Lastly it was recommended that the acoustics of classroom settings be improved so as to minimize environmental noises and other sounds that may interfere with the amplification of sounds.

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Children with hearing impairment have experienced discrimination from regular education. In the past, such children were institutionalised in separate classes or schools. According to Vayrynen (2000), most schools have been failing students with disabilities by denying them access to appropriate facilities. Children with hearing impairment have the right to be included in a least restrictive environment. Foster (1990) argues that to deny any child the opportunity to learn with their age mates age-mates and peers on grounds of an impairment is tantamount to jeopardising their later opportunity of living fully in a multi-cultural society. The Education Act (1987) in Zimbabwe stipulates that children with disabilities should be accommodated in ordinary schools for the purposes of learning. However, most teachers in Zimbabwean schools did not receive training on the teaching of children with impairments. It is on account of this that this present study attempts to gain insights into how children with hearing impairment benefit from learning in an inclusive environment with children whose hearing has no challenges. This article draws on a qualitative inquiry of teachers' experience in handling children with hearing impairment in their classrooms. A small sample of twenty (20) teachers comprising of ten (10) males and ten (10) females at Gomadoda cluster was chosen using purposive sampling. An interview schedule was used to collect data. Responses from respondents were captured and summarised to discern common patterns and then analysed and discussed. The study revealed that there are various problems met by children with hearing impairment in ordinary schools. The findings affirmed the assumption that most regular teachers lacked the necessary expertise and did not have adequate resources to handle children with hearing impairment. The study recommends that regular teachers undergo in-service programmes on how to effectively handle children with hearing

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The study explores the communication challenges faced by teacher trainees in teaching deaf learners and the opportunities that they present. A critical disabilities study approach within the qualitative paradigm was employed to collect interview data from 14 trainee teachers (6 were men and 8 women) and 5 of their specialist mentors (all of them were women) at 3 special schools in Zimbabwe. The trainees were aged 28-45. Data were analyzed using theme identification methods. Results showed that all the mentors and trainees without deaf assistants tended to teach using spoken language and even though they had no prior experience with them, they were suspicious of the use of deaf assistants, whom they saw as synonymous with sign language. Scepticism about using sign language was based on the idea that it was inadequate, would interfere with spoken language development, and would not enable learners to be included in a nondeaf world. It was also established that most of the mentors and ...

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One is learning when he is increasing the probability of making a correct response to a given stimulus. One has learned only when he is capable of giving an appropriate response. The 8.4.4 Curriculum of Education is followed in education of hearing impaired in special schools and units. Hence just as the case in regular education, the hearing impaired are expected to learn and perform well academically. Statement of the Problem was that children with hearing impairments are typically not educationally managed well to permit them compete satisfactorily in the society. The study aimed at investigating factors hindering effective learning of children who are hearing impaired in one special primary school and units in Meru North District in Eastern Province of Kenya. Education being a basic human right, children who are hearing impaired successful learning, needs to be emphasized and factors hindering it to be addressed. Literature was reviewed on trends in the education of children who...

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Roberto and Biology: A Case Study on Accommodations for Deafness

My name is Roberto and I am a premedical student majoring in biology. I have a severe-to-profound bilateral hearing loss and use hearing aids and speech reading (watching the movement of a person's lips) to maximize my communication skills. I have some knowledge of American Sign Language but not enough to effectively use a sign language interpreter as an accommodation.

Access Issues

My biology courses, as well as many other courses in science and mathematics, involve intensive lectures; some have interactive discussion sessions, and all of them make extensive use of advanced technical terms. Many of these terms are difficult to hear with hearing aids or to lip-read. I tried to use an FM amplification system (which through a microphone and transmitter worn by the instructor sends his or her words directly to my hearing aid) in these classes, but it was not helpful because of the nature of my hearing loss. If I miss information because of my hearing impairment, then I can't follow the lecture or adequately participate in discussion and ask questions. Note taking provides limited assistance since the notes are not verbatim, I can only review them after the class session, and sometimes the notes are available only one or two days after the class session. Note-taking assistance and front-row seating are adequate for me in nonscience and nonmathematics courses. Because the pace of instruction in science and mathematics is fast and the volume of material covered in each session is large, it is important that I have an adequate means to access the course lecture and discussion as it happens.

I contacted the office of disability services and requested the provision of real-time captioning in my science and mathematics classes. I told the counselor that I had tried various accommodations like note taking and the FM system but that I was still having difficulty with the lectures. The deaf services counselor reviewed my request and then approved it.

Real-time captioning as an accommodation involves having someone with adequate stenography training (often a court reporter) come to the class with me. The stenographer has a steno machine and laptop that is loaded with stenography software, and they sit next to me so I can see the monitor. When the instructor talks or others participate in class discussion, the stenographer enters all spoken words. The words spoken then appear very quickly on the monitor, and I can follow the discussion, ask questions, and, after class, get a hard copy of the notes. Alternatively, the office of disability services arranges for a stenographer at a remote site to provide the same service; in this situation, the instructor wears a wireless microphone that transmits the voice back over the same phone line that is used to instantly send back the real-time captions to the student with a laptop in the classroom. This alternative procedure is used when there is a shortage of qualified stenographers, there are scheduling difficulties, or it is the most cost-effective method to provide the accommodation.

This case study demonstrates the following:

• Students who are deaf or hard of hearing may have differing accommodation needs, and the accommodations may not be the same in all courses for the same student.
• Accommodation procedures and alternatives must be in place, or there must be a capacity to quickly make arrangements to implement the accommodation.
• There are advanced technical accommodations, such as real-time captioning, that may be available anywhere in the country when students and support staff are aware of the resources.
• Students who are deaf or hard of hearing and those with other sensory disabilities can compete in scientific and technical fields and careers.

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Case Study of a 5-Year-Old Boy with Unilateral Hearing Loss

Jan 15, 2015 | Pediatric Care | 0 |

Case Study | Pediatrics | January 2015  Hearing Review 

A reminder of what our tests really say about the auditory system..

By Michael Zagarella, AuD

How many times have I heard— and said myself—that the OAE is not a hearing test? How many times have I thought to myself that, just because a child passes their newborn hearing screening test, it does not mean they have normal hearing? This case brought those two statements front and center.

A 5-year-old boy was referred to me for a hearing test because he did not pass a kindergarten screening test in his right ear. His parents reported that he said “Huh?” frequently, and more recently they noticed him turning his head when spoken to. He had passed his newborn hearing screening, and he had experienced a few ear infections that responded well to antibiotics. The parents mentioned a maternal aunt who is “nearly totally deaf” and wears binaural hearing aids.

Initial Test Results

Otoscopic examination showed a clear ear canal and a normal-appearing tympanic membrane on the right side. The left ear canal contained non-occluding wax.

Tympanograms were within normal limits bilaterally. Unfortunately, otoacoustic emissions (OAE) testing could not be completed because of an equipment malfunction.

Behavioral testing with SRTs was taken, and I typically start with the right ear. The child seemed bright and cooperative enough for routine testing. I obtained no response until 80 dB.

I switched to the left ear and he responded appropriately. This prompted me to walk into the test booth and check the equipment and wires; everything was plugged in and looked normal. I tried SRTs again with the same results, even reversing the earphones. Same results. When the behavioral tests were completed, the results indicated normal hearing in his left ear and a profound hearing loss in his right ear.

The child’s parents were informed of these results, and we scheduled him to return for a retest in order to confirm these findings.

Follow-up Test

One week later, the boy returned for a follow-up test. The otoscopic exam was the same: RE = normal; LE = non-occluding wax.

Tympanograms were within normal limits. I added acoustic reflexes, which were normal in his left ear (80-90 dB), and questionable in his right ear (105-115 dB).

DPOAEs were present in both ears. The right ear was reduced in amplitude compared with the left, but not what I would expect to see with a profound hearing loss (Figure 1).

I repeated the behavioral tests with the same results that I obtained the first time (Figure 2). Bone conduction scores were not obtained at this time because I felt I was reaching the limits of a 5-year-old, and the tympanograms were normal on two occasions.

Recommendation to Parents

After completing the tests, I explained auditory dyssynchrony to the parents, and told them that this is what their son appeared to have. Since they were people with resources, I advised them to make an appointment at Johns Hopkins to have this diagnosis confirmed by ABR.

Johns Hopkins Results

The initial appointment at Johns Hopkins was at the ENT clinic. According to the report from the parents, the physician reviewed my test results and said it was unlikely that they were valid. She suggested they repeat the entire test battery before proceeding with an ABR. All peripheral tests were repeated with exactly the same results that I had obtained. The ABR was scheduled and performed, yielding:

“Findings are consistent with normal hearing sensitivity in the left ear and a neural hearing loss in the right ear consistent with auditory dyssynchrony (auditory neuropathy). The normal hearing in the left ear is adequate for speech and language development at this time.”

Additional Follow-up

The boy’s mother was not completely satisfied with the diagnosis or explanation. After she arrived home and mulled things over, she called Johns Hopkins and asked if they could do an MRI. The ENT assured her that it probably would not show anything, but if it would allay her concerns (and since they had good insurance coverage), they would schedule the MRI.

Further reading: Vestibular Assessment in Infant Cochlear Implant Candidates

Figure 1. DPOAEs of 5-year-old boy.

Findings of MRI. Evaluation of the right inner ear structures demonstrated absence of the right cochlear nerve. The vestibular nerve is present but is small in caliber. The internal auditory canal is somewhat small in diameter. There is atresia versus severe stenosis of the cochlear nerve canal. The right modiolus is thickened. The cochlea has the normal amount of turns, and the vestibule semicircular canals appear normal.

The left inner ear structures, cranial nerves VII and VIII complex, and internal auditory canal are normal. Additional normal findings were also presented regarding sinuses, etc.

Key finding: The results were consistent with atresia versus severe stenosis of the right cochlear nerve canal and cochlear nerve and deficiency described above.

The Value of Relearning in Everyday Clinical Practice

Figure 2. Follow-up behavioral test of 5-year-old boy.

According to the MRI, the cochlea on the right side is normal—which would explain the present DPOAE results. The cochlear branch of the VIIIth Cranial Nerve is completely absent, which would explain the absent ABR result and the profound hearing loss by behavioral testing.

This case has certainly caused me to re-evaluate what I think and say about my test findings. How many times have I heard—and said myself!—that the OAE is not a hearing test? How many times have I thought to myself that, just because a child passes their newborn hear- ing screening test, it does not mean that they have normal hearing?

This case has surely brought those two statements front and center. In addition, what about auditory neuropathy? In about 40 years of testing, I had never seen a case that I was convinced was AN. Naturally, I was somewhat skeptical about this disorder: Is it real, or does it reside in the realm of the Yeti. (Personal note to Dr Chuck Berlin: I truly don’t doubt you, but I do like to see things for myself!)

Finally, this case only reinforces my trust in “mother’s intuition” and the value of deferring to the sensible requests of parents. If she had not felt uneasy about what she had been told at one of the most prestigious clinics in the country, the actual source of this problem would not have been discovered.

So what? Does any of this really make a difference? The bottom line is we have a 5-year-old boy with a unilateral profound hearing loss. How important is it that we know why he has that loss? From a purely clinical standpoint, I think that it is poignant because it brings home the importance of understanding what our tests really say about the hearing mechanism and auditory system (ie, is working or not working?).

And although it may not make a large difference in the boy’s current treatment plan, I do know that the boy’s mother is grateful for understanding the reason for her son’s hearing loss and that it’s at least possible the boy may benefit from this knowledge in the future.

Michael Zagarella, AuD, is an audiologist at RESA 8 Audiology Clinic in Martinsburg, WVa.

Correspondence can be addressed to HR or or Dr Zagarella at:  [email protected]

Citation for this article: Zagarella M. Case study of a 5-year-old boy with unilateral hearing loss. Hearing Review . 2015;22(1):30-33.

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Practical Applications of AI in Education for Accessibility

2024-05-28 | By Orcam Staff

The intersection of artificial intelligence (AI) and education is a rapidly evolving field. It holds immense potential for transforming learning experiences, particularly for students with diverse needs.

AI in education for accessibility is a topic of growing interest. It focuses on leveraging AI tools and solutions to enhance accessibility in learning environments.

This article delves into the practical applications of AI in education. It highlights how AI is breaking down barriers and creating inclusive learning spaces.

We will explore various AI tools that are making education more accessible. From real-time captioning to adaptive learning platforms, AI is revolutionizing the way we approach education.

We will also touch upon the ethical considerations and data privacy issues surrounding the use of AI in education.

Join us as we navigate the exciting landscape of AI in education for accessibility. Discover how AI is shaping the future of inclusive learning.

Understanding AI in Education for Accessibility

AI in education means using smart computer programs to improve teaching and learning. These programs can adjust lessons to fit each student's needs.

Using AI in education helps make learning more inclusive and accessible, especially for students with disabilities.

The following are some of the ways AI is being used to enhance accessibility in education:

Providing real-time captioning and transcription services

Creating adaptive learning platforms that adjust to individual learning styles

Developing assistive technologies for visually and hearing-impaired students

The Significance of AI for Learners with Disabilities

AI has the potential to revolutionize education for learners with disabilities. It can provide customized learning experiences that cater to individual needs and abilities.

For instance, AI tools can convert text to speech for visually impaired students. They can also provide real-time captioning for students with hearing impairments.

These AI tools help make learning easier and more accessible for students with disabilities, allowing them to join in and learn just like their classmates.

Overcoming Educational Barriers with AI

AI is playing a crucial role in overcoming educational barriers. It is helping to create a more inclusive and equitable learning environment.

AI-powered adaptive learning platforms are online tools that change how they teach based on how a student learns best.

They can provide personalized learning pathways that cater to each student's strengths and weaknesses.

Moreover, AI can facilitate language translation and support English as a Second Language (ESL) learners. This can help break down language barriers and make education more accessible to all.

AI Tools Enhancing Learning Support

AI tools are playing a pivotal role in enhancing learning support. They are providing innovative solutions to address the diverse needs of learners.

One of the key areas where AI is making a significant impact is in real-time captioning and transcription services. These tools are particularly beneficial for students with hearing impairments.

AI is also revolutionizing assistive technologies for visually impaired students. It is helping to create more inclusive learning environments.

Moreover, AI is at the forefront of developing adaptive learning platforms. These platforms are transforming education by providing personalized learning experiences.

Real-time Captioning and Transcription Services

AI-powered real-time captioning and transcription services are a game-changer in education. They are making learning more accessible for students with hearing impairments.

AI tools can add captions to live classes and discussions right away. They can also turn spoken words into written text, helping students keep up with the lessons.

By providing real-time captioning and transcription, AI is ensuring that all students can participate fully in the learning process.

Accessibility Technology for Visual and Hearing Impairments

AI is playing a crucial role in developing accessibility technologies for visually and hearing-impaired students. These technologies are enhancing accessibility and inclusivity in education.

For instance, AI-powered tools can convert text to speech for visually impaired students. They can also provide audio descriptions for visual content.

Similarly, AI can enhance the learning experience for students with hearing impairments. It can provide real-time captioning and sign language interpretation.

These AI solutions are not only enhancing accessibility but also empowering students with disabilities to participate fully in the learning process.

Adaptive Learning Platforms and Personalized Education

AI is at the forefront of developing adaptive learning platforms. These platforms use AI algorithms to adjust to individual learning styles.

They can analyze a student's performance and provide personalized learning pathways. This can help cater to each student's strengths and weaknesses.

Moreover, these platforms can provide immediate feedback and assessment. This can help students understand their progress and areas needing improvement.

By providing personalized and accessible education, AI is helping to create a more inclusive and equitable learning environment.

Ethical Considerations and Data Privacy in Educational AI

As AI continues to transform education, ethical considerations and data privacy have become paramount. These issues are critical to ensuring the responsible use of AI in education.

AI systems often require large amounts of data to function effectively. This data can include sensitive information about students' learning habits and performance. Therefore, it's crucial to have robust data privacy measures in place.

We need to make sure AI is used in a fair and open way, with clear rules to protect everyone's privacy. These principles can help ensure that AI tools are used to enhance learning and not to disadvantage or discriminate against certain groups of students.

Case Studies: AI's Impact in Educational Settings

AI's impact on education is not just theoretical. It's already being felt in classrooms around the world. Let's explore some case studies that highlight the transformative power of AI in education.

Supporting ESL Learners and Language Translation

AI has been a game-changer for English as a Second Language (ESL) learners. Tools like Microsoft's Immersive Reader use AI to translate text into different languages, making content more accessible for non-native speakers. This technology is helping to break down language barriers in education.

AI-Driven Analytics for Student Progress

AI is also revolutionizing the way we track student progress. For instance, AI-powered platforms like BrightBytes analyze student data to provide insights into learning patterns. This allows educators to identify areas where students may need additional support, enhancing the learning experience.

The Future of AI in Education and Accessibility

The future of AI in education and accessibility looks promising. As technology continues to evolve, we can expect to see even more innovative AI solutions that enhance learning for all students.

However, it's important to remember that AI is not a magic bullet. It's a tool that can be used to improve education, but it's not a substitute for good teaching and supportive learning environments.

Challenges and Limitations of AI in Education

Despite its potential, AI in education also faces challenges. One of the main issues is the digital divide. Not all students have access to the technology needed to benefit from AI tools.

Moreover, there are concerns about data privacy and the ethical implications of using AI in education. These issues need to be addressed to ensure that AI is used responsibly and effectively.

The Road Ahead: Potential Developments in AI for Education

Looking ahead, we can expect to see AI playing an even bigger role in education. From personalized learning pathways to AI-powered tutoring systems, the possibilities are endless.

However, for these developments to be successful, it's crucial that educators, policymakers, and AI developers work together. By collaborating, we can ensure that AI is used to create inclusive, accessible, and effective learning environments for all students.

Conclusion: Embracing AI for Inclusive Learning

In conclusion, AI holds immense potential to revolutionize education and make it more accessible. It's a powerful tool that can help overcome barriers and create inclusive learning environments.

However, it's crucial that we approach AI with a critical eye, ensuring it's used ethically and effectively to truly enhance education for all.

Deaf and hard-of-hearing students need more support from their universities: South Africa study

A djusting to university life tends to be tough no matter who you are. But what happens when deafness makes the usual demands even more difficult? Deaf students or those who are hard of hearing need extra accessibility measures to ensure they're able to participate in even basic academic activities like lectures and tutorials. Tonny Matjila, who studied the experiences of Deaf and hard-of-hearing students at one large South African university, tells The Conversation Africa what he learned.

How many Deaf and hard-of-hearing students are enrolled in South African universities?

We do not have accurate statistics for students who are Deaf and hard of hearing in higher education in South Africa. It is known that less than 1% of the student population has disabilities, with no real distinction between visual impairment, hearing, mobility issues and so on.

Statistics for the population are easier to come by: the country's 2011 Census reported that there were more than 4 million deaf or hard-of-hearing people in the whole country; the figures were nearly identical in the 2022 Census .

Many students in tertiary institutions choose not to disclose their hearing challenges because they worry about how people might react.

Of course this fear isn't true for all students who have hearing-related difficulties. Some identify as proudly Deaf, using the capital "d" because they don't see themselves as disabled. Instead, their challenge is a language barrier because they speak South African Sign Language rather than a verbal language.

What was the purpose of your research?

This study built on previous research I'd conducted to understand deaf students' experiences in higher education.

Here, I was evaluating the support services for students at one university. I wanted to know what support was offered to deaf students and to find out whether they were using these services.

I sent questionnaires to just more than 100 students who were deaf or hard of hearing, as well as 123 staff members. I also interviewed eight students and 11 staff members.

What did the participants tell you about their experiences?

Some of the participants used assistive devices like hearing aids or cochlear implants . Some had the use of just one ear; others were profoundly deaf.

My interviewees felt abandoned by the university. In all cases, they had identified themselves as deaf or hard of hearing when they registered. The institution admitted them knowing that they had hearing challenges. But then, the students told me, they were left to fend for themselves without the support they were promised. For example they couldn't benefit from career counseling, funding and tutoring opportunities and internships.

It's not that these services don't exist. But students weren't given follow-up information about where to find them. Students who sought out services found there were language barriers. There were no sign language options, nor was there anyone who spoke their home languages if they had some hearing ability.

Students were unable to participate in online events like tutorials, lectures or events. Where slides were used, there were no captions or sign language interpreters.

This led to feelings of exclusion and isolation. One respondent told me:

"People who hear have everything they need; we depend on the interpreters, we are not catered to, and it is lonely."

The students told me that the university developed, planned and implemented interventions for them without consulting them. They wanted to be involved in solving their own challenges.

The staff members I interviewed didn't know how to assist students who were deaf or hard of hearing. They usually referred these students to the university's disability unit, which has sign language interpreters on staff. But while interpreters can help with basic language issues, most find it difficult to interpret academic terms from lectures.

The staff tried to communicate through notes on paper. Deaf students found this stressful.

What can be done to improve students' experiences?

Though my research focused on one university, the problems I've identified are hardly unique.

It's clear that the country's policy framework on disability for post-school education and training, introduced in 2018, is not being taken seriously or enforced by institutions and that the department of higher education and training isn't monitoring how it's being applied (or not).

There are ways to improve the situation.

First, universities should review their language policies, especially now that Sign Language has been made the country's 12th official language.

It could, for instance, become official policy at the institution that staff must learn South African Sign Language, or that universities must employ far more interpreters than they currently do.

Communication channels should be made accessible, too. Universities should provide sign language interpreters, real-time captioning, and other assistive technologies to give deaf and hard-of-hearing students access to lectures, seminars and other academic activities. Visual or audio learning material should include captions, transcripts and other alternative formats.

There needs to be specialized academic support: tutoring services, study skills workshops, and academic advising tailored to the specific needs of deaf and hard-of-hearing students. This will help them navigate the challenges of higher education and achieve their academic goals. The curriculum should be developed with the students and not for them. This would allow alternative tests, assignments and exams without compromising university standards.

Also, universities should actively engage with the broader Deaf community, collaborating with Deaf organizations such as the Deaf Federation of South Africa to promote cultural events and activities that celebrate Deaf culture and foster a sense of belonging for students.

Lastly, it is essential for universities to provide internship opportunities and job placement to help deaf and hard-of-hearing students make the transition to the workforce. In that way, they will see the value of completing their qualifications.

This article is republished from The Conversation under a Creative Commons license. Read the original article .

Provided by The Conversation

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• Systematic Review
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• Published: 20 May 2024

Prevalence of hearing impairment in neonatal encephalopathy due to hypoxia-ischemia: a systematic review and meta-analysis

• Dinesh Pawale 1 ,
• Anurag Fursule 1 ,
• Jason Tan 1 , 2 ,
• Deepika Wagh 1 , 2 ,
• Sanjay Patole 2 , 3 &
• Shripada Rao 1 , 2  

Pediatric Research ( 2024 ) Cite this article

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Metrics details

This systematic review was undertaken to estimate the overall prevalence of hearing impairment in survivors of neonatal HIE.

PubMed, EMBASE, CINAHL, EMCARE and Cochrane databases, mednar (gray literature) were searched till January 2023. Randomized controlled trials and observational studies were included. The main outcome was estimation of overall prevalence of hearing impairment in survivors of HIE.

A total of 71studies (5821 infants assessed for hearing impairment) were included of which 56 were from high income countries (HIC) and 15 from low- or middle-income countries (LMIC). Overall prevalence rate of hearing impairment in cooled infants was 5% (95% CI: 3–6%, n  = 4868) and 3% (95% CI: 1–6%, n  = 953) in non-cooled HIE infants. The prevalence rate in cooled HIE infants in LMICs was 7% (95% CI: 2–15%) and in HICs was 4% (95% CI: 3–5%). The prevalence rate in non-cooled HIE infants in LMICs was 8% (95% CI: 2–17%) and HICs was 2% (95% CI: 0–4%).

Conclusions

These results would be useful for counseling parents, and in acting as benchmark when comparing institutional data, and while monitoring future RCTs testing new interventions in HIE. There is a need for more data from LMICs and standardization of reporting hearing impairment.

The overall prevalence rate of hearing impairment in cooled infants with HIE was 5% (95% CI: 3–6%) and 3% (95% CI: 1–6%) in the non-cooled infants.

The prevalence rate in cooled HIE infants in LMICs was 7% (95% CI: 2–15%) and in HICs was 4% (95% CI: 3–5%).

The prevalence rate in non-cooled HIE infants in LMICs was 8% (95% CI: 2–17%) and HICs was 2% (95% CI: 0–4%).

These results would be useful for counseling parents, and in acting as benchmark when comparing institutional data, and while monitoring future RCTs testing new interventions in HIE.

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Introduction.

Hypoxic ischemic encephalopathy (HIE) is a leading cause of neonatal brain injury, with an incidence of 1.5 per 1000 live births in developed countries and 2.3–26.5 per 1000 live births in lower and middle-income countries. 1 , 2 The sequelae of HIE encompass motor deficits, intellectual disability, and hearing and vision impairments. 3 , 4 , 5 , 6 Hearing loss has the potential to hinder a child’s linguistic progress, communication abilities, social wellbeing and overall quality of life, especially in socio-demographically disadvantaged children 7 , 8 , 9 Despite its significance, the overall prevalence of hearing impairment in survivors of HIE remains unclear. The 2013 Cochrane meta-analysis of seven Randomized controlled trials (RCTs) found that the incidence of hearing impairment was 3.8% (15/396) among survivors who received hypothermia and 5.8% (19/324) in those who received normothermia. 4 The results of the Cochrane review suggested that there was no significant impact of cooling on hearing impairment (RR 0.66, 95% CI: 0.35, 1.26). 4 The recent network meta-analysis included only seven RCTs evaluating hearing impairment, but the incidence of hearing impairment in neonatal HIE was not reported. 10 The other recent systematic reviews did not report on hearing outcomes. 11 , 12 , 13 While managing an infant with HIE, an important question that clinicians and parents face is “what are the chances of developing hearing impairment if the infant were to survive?”. To answer that question, it is essential to know the prevalence rates of hearing impairment in infants with HIE based on the current literature. Such information would be useful for counselling parents, and allocating resources for early intervention and in acting as benchmark when comparing instituitional data. Hence, this systematic review was undertaken to estimate the overall prevalence of hearing impairment in survivors of neonatal HIE.

Guidelines from the Joanna Biggs Institute were followed for conducting and reporting this systematic review. 14 Ethics approval was not required. The protocol was registered in PROSPERO (CRD42022335943).

Literature search

MEDLINE through PubMed, Embase, CINAHL, Emcare and Cochrane databases were searched in January 2023. Gray literature was searched through Mednar ( https://mednar.com ). Two reviewers conducted the literature search independently. The reference lists of included studies and other relevant articles were searched to identify additional studies. No language restrictions were applied.

MEDLINE was searched through PubMed using the following search terms:

((((((HIE) OR (hypoxic ischemic encephalopathy)) OR (birth asphyxia)) OR (perinatal asphyxia)) OR (neonatal encephalopathy)) AND ((((((((((deafness) OR (hearing loss)) OR (hearing impairment)) OR (sensorineural deafness)) OR (sensorineural hearing loss)) OR (sensorineural hearing impairment)) OR (auditory dysfunction)) OR (auditory impairment)) OR (cochlear implant)) OR (outcome))) OR ((hypoxic ischemic encephalopathy) AND (disability)).

The automatic mapping system of PubMed expanded it to the following terms:

((“HIE” OR (“hypoxic ischemic encephalopathy” OR “hypoxia ischemia, brain” OR (“hypoxia ischemia” AND “brain”) OR “brain hypoxia-ischemia” OR (“hypoxic” AND “ischemic” AND “encephalopathy”) OR “hypoxic ischemic encephalopathy”) OR (“asphyxia neonatorum” OR (“asphyxia” AND “neonatorum”) OR “asphyxia neonatorum” OR (“birth” AND “asphyxia”) OR “birth asphyxia”) OR ((“perinatal” OR “perinatally” OR “perinatals”) AND (“asphyxia” OR “asphyxia” OR “asphyxias”)) OR ((“infant, newborn” OR (“infant” AND “newborn”) OR “newborn infant” OR “neonatal” OR “neonate” OR “neonates” OR “neonatality” OR “neonatals” OR “neonate s”) AND (“brain diseases” OR (“brain” AND “diseases”) OR “brain diseases” OR “encephalopathies” OR “encephalopathy”))) AND (“deafness” OR “deafness” OR “deafnesses” OR (“hearing loss” OR (“hearing” AND “loss”) OR “hearing loss”) OR (“hearing loss” OR (“hearing” AND “loss”) OR “hearing loss” OR (“hearing” AND “impairment”) OR “hearing impairment”) OR (“hearing loss, sensorineural” OR (“hearing” AND “loss” AND “sensorineural”) OR “sensorineural hearing loss” OR (“sensorineural” AND “deafness”) OR “sensorineural deafness”) OR (“hearing loss, sensorineural” OR (“hearing” AND “loss” AND “sensorineural”) OR “sensorineural hearing loss” OR (“sensorineural” AND “hearing” AND “loss”)) OR (“hearing loss, sensorineural” OR (“hearing” AND “loss” AND “sensorineural”) OR “sensorineural hearing loss” OR (“sensorineural” AND “hearing” AND “impairment”) OR “sensorineural hearing impairment”) OR (“hearing disorders” OR (“hearing” AND” disorders”) OR “hearing disorders” OR (“auditory” AND “dysfunction”) OR “auditory dysfunction”) OR ((“auditorially” OR “auditory”) AND (“impair” OR “impaired” OR “impairement” OR “impairements” OR “impairing” OR “impairment” OR “impairments” OR “impairs”)))) OR ((“hypoxic ischemic encephalopathy” OR “hypoxia ischemia, brain” OR (“hypoxia ischemia” AND “brain”) OR “brain hypoxia-ischemia” OR (“hypoxic” AND “ischemic” AND “encephalopathy”) OR “hypoxic ischemic encephalopathy”) AND (“disabilities” OR “disability” OR “disabled persons” OR (“disabled” AND “persons”) OR “disabled persons” OR “disabled” OR “disablement” OR “disablements” OR “disabling” OR “disability”)). Similar terms were used for other databases.

Inclusion criteria

Eligible studies from year 2000 onwards which reported the incidence of hearing impairment in survivors of HIE were included. Studies in which neonates received hypothermia as standard of care or as part of clinical trial were included. Similarly, all studies in which neonates with HIE received normothermia as standard of care or as part of clinical trial were included. Studies published from year 2000 onwards were included to ensure appropriate comparison and contemporaneousness of the data, considering the publication of the first pilot study on therapeutic hypothermia in HIE at the time. 15 Review articles, editorials, case reports, letters and commentaries were excluded.

The diagnosis of hearing impairment could have been based on the auditory brainstem response (ABR) or otoacoustic emissions (OAE) prior to discharge or subsequent audiology assessments or could have been reported as part of formal developmental assessments.

Quality assessment

We used the quality assessment tool from the Joanna Briggs Institute. 16 which has the following criteria: (1) Was the sample frame appropriate to address the target population? (2) Was the study population sampled in an appropriate way? (3) Was the sample size adequate? (4) Were the study subjects and settings described in detail? (5) Was the data analysis conducted with sufficient coverage of the identified sample? (6) Were valid methods used for identification of the condition? (7) Was the condition measured in a standard, reliable way for all the participants? (8) Was there appropriate statistical analysis? (9) Was the response rate adequate, and if not, was the low response rate managed appropriately? The criteria were rated as either yes, no, not clear, or not applicable.

Data extraction

Two reviewers independently extracted the data using a prespecified data collection form. Information about the study design and outcomes was verified by three reviewers independently. Disagreements were resolved through discussions. Where necessary, authors of the included studies were contacted, requesting additional information from their studies.

Data synthesis

Meta-analysis was conducted using Stata 18 (StataCorp, 4905 Lakeway Drive, College Station, Texas 77845 USA). 17 Using the metaprop command to derive the pooled estimation of prevalence. 18 The Freeman–Tukey Double Arcsine Transformation was used to stabilize the variances. The prevalence rates of hearing impairment in individual studies were computed using the formula: (number of infants with hearing impairment/number of infants assessed for hearing impairment). We used the absolute number of observed events and calculated the proportions and 95% confidence intervals (CIs), assuming a binomial distribution. A logistic normal random effects model was fitted. Heterogeneity was assessed by using the χ2 test and the I 2 statistic. In addition, the proportions with their 95% CI values from individual studies were also presented in a forest plot. Funnel plots were used for assessing publication bias. Eggers’s test was used as formal test of funnel plot asymmetry and publication bias. Summary estimates of prevalence rates of hearing impairment were calculated separately for cooled and non-cooled neonates.

Figure  1 provides details of the study selection process. Included studies were segregated into two groups based on whether infants received cooling or not. Infants in the non-cooled arms of RCTs were grouped together with observational studies in which infants were not cooled. Similarly, infants in the cooled arms of RCTs were grouped together with observational studies wherein infants were cooled. A total of 71 studies were included in the systematic review, of which 52 provided information on cooled infants, seven provided information on non-cooled infants and the remaining 11 provided information on both cooled and non-cooled infants in the published manuscripts. Upon request, one author provided information from their published RCT. 19

Preferred reporting items for systematic reviews and meta-analyses flow diagram.

Studies in which infants with HIE were cooled

A total of 64 studies reported the outcomes on hearing assessment in cooled HIE infants (Table  1 ). 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 Amongst included studies, 15 were RCTs 19 , 22 , 31 , 32 , 35 , 43 , 47 , 60 , 61 , 64 , 70 , 72 , 73 , 74 , 75 and 49 were observational studies. 20 , 21 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 33 , 34 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 44 , 45 , 46 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 62 , 63 , 65 , 66 , 67 , 68 , 69 , 71 , 72 , 76 , 77 , 78 , 79 , 80 , 81 , 82 The total sample size was 7990 cooled infants, out of which 4868 were assessed for hearing impairment. The median sample size in the included studies was 61 (IQR 27–104; range: 5–1484).

Full information on the total number of survivors from all included studies was not available. However, based on the available data from 38 studies where such information was available, the median follow up rates among survivors in individual studies were 96.3% (IQR: 86.3–100%, range: 13.5–100%).The median age at reported follow up was 22 months (IQR: 18–24 months). In the majority of studies, hearing impairment was reported as a part of developmental assessment using validated tools such as Bayley or Griffiths Scales. Fifteen studies reported about the diagnostic tools used for hearing impairment assessment, with ABR or OAE being the commonly used tools. 19 , 20 , 26 , 33 , 36 , 44 , 48 , 50 , 51 , 58 , 66 , 72 , 78 , 79 , 82 Five studies reported about diagnosis of hearing impairment before initial discharge from hospital. 19 , 26 , 48 , 66 , 79

Studies in which infants with HIE were not cooled

A total of 19 studies reported the outcome of hearing impairment in non-cooled HIE infants (Table  2 ). 19 , 22 , 31 , 35 , 43 , 47 , 60 , 64 , 72 , 73 , 74 , 75 , 83 , 84 , 85 , 86 , 87 , 88 , 89 Amongst included studies, 12 were non-cooled arms of RCTs. 19 , 22 , 31 , 35 , 43 , 47 , 60 , 64 , 72 , 73 , 74 , 75 and seven were observational studies. 83 , 84 , 85 , 86 , 87 , 88 , 89 The total sample size was 1402 infants, out of which 953 were assessed for hearing impairment. The median sample size in the included studies was 61 (IQR 22–110; range: 3–206). Full information on the total number of survivors from all included studies was not available. Based on 11 studies on non-cooled infants in which such information was available, median follow-up rates amongst survivors in individual studies was 100% (IQR: 83.3–100%, Range: 29.3–100%). In majority of studies, hearing impairment was reported as a part of developmental assessment. The median age at reported follow up was 20 months (IQR: 13–22 months). Three studies reported information about the diagnostic tools used for hearing impairment assessment, all of them using the ABR. 19 , 72 , 84 .

Meta-analysis

The overall prevalence rate of hearing impairment among survivors of cooled HIE infants was 5% (95% CI: 3–6%; I 2  = 59.88%, Fig.  2 ). The prevalence rate of hearing impairment in survivors of non-cooled HIE infants was 3% (95% CI: 1–6%; I 2  = 51.42%, Fig.  3 ).

Forrest plot of studies with cooled HIE infants.

Forrest plot of studies with non-cooled HIE infants.

Subgroup analysis

To explore heterogeneity, a subgroup analysis was conducted based on income level of countries. 90 Out of 71 included studies, 15 (21.1%) were conducted in low or middle-income countries (LMICs), 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 84 , 88 whereas 56 (78.8%) were from high-income countries (HICs). 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 83 , 85 , 86 , 87 , 89 The prevalence rate of hearing impairment in cooled infants in LMICs was 7% (95% CI: 2–15%) and in HICs was 4% (95% CI: 3–5%) (Fig.  2 ). The prevalence rate in non-cooled infants in LMICs was 8% (95% CI: 2–17%) and in HICs was 2% (95% CI: 0–4%) (Fig.  3 ).

Publication bias

The funnel plots and the p values on the Egger’s test for the studies with cooled infants ( P  = 0.023) suggested publication bias while funnel plot for the studies with non-cooled infants ( P  = 0.103) did not suggest statistically significant publication bias (Figs.  4 and 5 ).

Funnel plot of studies with cooled HIE infants.

Funnel plot of studies with non-cooled HIE infants.

Sensitivity analysis

In further explore heterogeneity, the following analyses were conducted.

Prevalence of hearing impairment was estimated separately for selective head cooling, whole body cooling and mixed cooling. The results were similar with a prevalence between 4 and 6%. (Table  3 ).

In many studies, cooling was initiated even in infants with Stage I HIE. 21 , 31 , 37 , 38 , 40 , 43 , 46 , 48 , 54 , 55 , 65 , 68 , 72 , 76 , 83 , 84 , 87 The inclusion of such infants in the meta-analysis could have resulted in an underestimation of the overall prevalence rates in moderate to severe HIE. Hence, we conducted a sensitivity analysis by analyzing them separately. The overall prevalence was 5% in moderate to severe HIE whereas it was 3% in studies that had included infants even with mild HIE (Table  3 ).

The prevalence of hearing impairment in cooled HIE surviving infants among studies that had ≥80% follow-up was 6% and in <80% follow-up was 4%. The prevalence of hearing impairment in non-cooled HIE infants with studies that had more than ≥80% follow-up was 1% and that in <80% follow-up was 7% (Table  3 ).

The prevalence of hearing impairment in cooled HIE surviving infants among studies that had mentioned the use of BERA/OAE was 9%. The prevalence of hearing impairment was 4% where studies reported it as part of formal developmental assessment. The prevalence in non-cooled HIE surviving infants among studies that had mentioned the use of BERA/OAE was 3%. The prevalence of hearing impairment was 4% where studies reported it as part of formal developmental assessment (Table  3 ).

Risk of bias

The risk of bias was low in the majority of the domains in the included studies (Tables  4 and 5 ).

In this systematic review that included 5821 infants from 71 studies, the overall prevalence rate of hearing impairment in surviving cooled infants with HIE was 5% [(95% CI 3–6%), n  = 4868 from 64 studies)] and 3% [(95% CI 1–6%), n  = 953 infants from 19 studies] in non-cooled infants during the same time period. These rates are significantly higher than the global prevalence of 0.1–0.4% (1–4 per 1000 live births) in general neonatal population 91 and 1.57% (15.7 per 1000) in NICU population. 92 These results would be useful as a benchmark for comparing institutional data, counseling parents and guiding policy makers. 93 The results will also be useful for data and safety monitoring committees (DSMCs) of randomized controlled trials evaluating  potentially ototoxic drugs in neonates with HIE. 94 The dose finding study of bumetanide for neonatal seizures (NEMO trial) was stopped prematurely by the DSMC due insufficient efficacy and a potential increased prevalence of hearing loss (3/11 or 27%) in infants with HIE who had received bumetanide. 58 In that context, the results of our meta-analysis have the potential to guide the DSMCs while monitoring new interventions in neonates with HIE.

Our overall results are similar to the Cochrane meta-analysis of seven RCTs that found the incidence to be 3.8% (15/396) among survivors who had received hypothermia and 5.8% (19/324) in those who received normothermia. 4 Even though our study was not about comparing cooling versus normothermia, the prevalence rates of 5% [(95% CI 3–6%), and 3% [(95% CI 1–6%) respectively with overlapping confidence intervals suggests that cooling may not have an impact on hearing impairment, similar to the findings of the Cochrane review.

Our meta-analysis found a higher prevalence of hearing impairment in LMICs compared to HICs. The probable reasons for this finding include the use of ototoxic antibiotics without optimal monitoring of drug levels, and higher incidence of sepsis, low birthweight and growth restricted infants in LMICs. Even though the burden of HIE is more in LMICs, there are very limited number of studies from such countries reporting on hearing impairment. Institutions managing neonates with HIE should be provided adequate resources to enable audiology and long-term developmental assessments.

This review highlights the inconsistency among studies in the reporting various aspects of hearing impairment. In the majority of studies, screening or diagnostic tools used for hearing impairment and timing of assessment were not mentioned. In many studies, the severity of hearing impairment was categorized as not requiring amplification, corrected by amplification, or not corrected by amplification. 21 , 22 , 24 , 32 , 34 , 35 , 37 , 42 , 43 , 45 , 46 , 47 , 52 , 56 , 60 , 61 , 64 , 72 , 73 , 75 , 80 , 83 However, in some studies, the severity was more objectively classified based on the level of hearing threshold in decibels. 26 , 32 , 35 , 48 , 50 , 51 , 58 , 84 Details regarding the laterality of hearing impairment were found in only 10 studies, 26 , 33 , 35 , 50 , 51 , 58 , 65 , 76 , 79 , 84 while the severity was addressed in only 15 studies. 20 , 26 , 28 , 37 , 39 , 40 , 42 , 43 , 51 , 56 , 58 , 60 , 64 , 67 , 72 , 89 Even among the subset of fifteen studies, only three provided a grading system for hearing impairment severity. 26 , 51 , 60 Given the importance of hearing in acquiring language and communication skills, future studies should incorporate crucial information such as the age at screening, age at definitive diagnosis, tools used for screening and definitive diagnosis, severity, laterality, age at intervention, and type of intervention to enable comprehensive understanding. A standardized approach would facilitate more accurate comparisons across studies and enable healthcare providers to develop evidence-based strategies for the prevention and management of hearing impairment in this population.

The limitations of the systematic review include the presence of heterogeneity, insufficient information on the severity and laterality of hearing impairment and on the methods used for assessing hearing. The strengths of our review include the robust and comprehensive literature search, large sample size, inclusion of RCTs as well as real life data, formal assessment of publication bias and exploration of heterogeneity through sensitivity and subgroup analyses.

The overall prevalence rate of hearing impairment in cooled surviving infants was 5% (95% CI 3–6%), and 3% (95% CI 1–6%) in the non-cooled surviving infants with HIE. These results would be useful for counseling parents, and in acting as benchmark when comparing institutional data, and while monitoring future RCTs testing new interventions in HIE.

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D.P., A.F., J.T., and D.W. did the review of literature. S.R., D.P., and A.F. did the meta-analyses. D.P., and A.F. coordinated the investigator group and wrote the first draft of the paper. S.R. and S.P. advised on data analysis and edited the paper. S.R., J.T., and S.P. contributed to successive versions of the paper. S. Rao was responsible for overall supervision of the project from inception till publication.

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Correspondence to Shripada Rao .

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Pawale, D., Fursule, A., Tan, J. et al. Prevalence of hearing impairment in neonatal encephalopathy due to hypoxia-ischemia: a systematic review and meta-analysis. Pediatr Res (2024). https://doi.org/10.1038/s41390-024-03261-w

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Received : 01 March 2024

Revised : 17 April 2024

Accepted : 29 April 2024

Published : 20 May 2024

DOI : https://doi.org/10.1038/s41390-024-03261-w

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