International Journal of Audiology 2015; 54: 308–315
Original Article
Hearing aid and hearing assistance technology use in Aotearoa/New Zealand Rebecca J. Kelly-Campbell & Kamea Lessoway Department of Communication Disorders, University of Canterbury, Christchurch, New Zealand
Abstract Objective: The purpose of this study was to describe factors that are related to hearing aid and hearing assistance technology ownership and use in Aotearoa/New Zealand. Design: Adults with hearing impairment living in New Zealand were surveyed regarding health-related quality of life and device usage. Audiometric data (hearing sensitivity and speech in noise) were collected. Study sample: Data were obtained from 123 adults with hearing impairment: 73 reported current hearing-aid use, 81 reported current hearing assistance technology use. Results: In both analyses, device users had more difficulty understanding speech in background noise, had poor hearing in both their better and worse hearing ears, and perceived more consequences of hearing impairment in their everyday lives (both emotionally and socially) than non-hearing-aid users. Discriminant analyses showed that the social consequences of hearing impairment and the better ear hearing best classified hearing aid users from non-users but social consequences and worse ear hearing best classified hearing assistance technology users from non-users. Conclusions: Quality of life measurements and speech-in-noise assessments provide useful clinical information. Hearing-impaired adults in New Zealand who use hearing aids also tend to use hearing assistance technology, which has important clinical implications.
Key Words: Hearing aids; hearing assistance technology; speech in noise; New Zealand; hearing assistive devices It is estimated that one in six New Zealanders experiences hearing impairment (National Foundation for the Deaf). The most detailed and recent prevalence data regarding hearing impairment and hearing-aid use in New Zealand (“Aotearoa” in te reo Ma¯ ori) was a population survey associated with the 2001 census (Greville, 2005). This survey reports that the prevalence of hearing impairment in New Zealand is approximately 10.3%. When considering the entire hearing-impaired population of New Zealand, 8% comprise children under the age of 14 years, while approximately 33% of hearing-impaired people in New Zealand are adults between the ages of 45 and 64 years. There is a sex disparity in the prevalence of hearing impairment in New Zealand: the overall male to female ratio of people with hearing impairment is 1.37:1.0. It is estimated that between 30% and 50% of the prevalence of hearing impairment in New Zealand can be attributed to noise exposure (Thorne et al, 2008). According to Greville (2005), the prevalence of hearing impairment for people aged 65 years and older of New Zealand Ma¯ ori ancestry is 24.4% while the prevalence of hearing impairment for people aged 65 years and older of non-Ma¯ ori ancestry is 22.0%. Finally, there is an income disparity in New Zealand between adults
with a hearing impairment and the total adult population. In 2001, 67% of adults with hearing impairment had personal incomes below $20 000, compared with 52% of the total adult population (Greville, 2005). The negative psychosocial consequences for adults living with hearing impairment are varied, and have been well documented in the literature internationally. Amongst the more common consequences of hearing impairment are difficulties with communication, social and emotional isolation, greater dysfunction for physical and mental health, and a negative impact on perception of overall quality of life (Chia et al, 2007; Dalton et al, 2003; Keller et al, 1999; Mulrow et al, 1990; Strawbridge et al, 2000). Hearing impairment can also have negative consequences in the workforce (Jennings & Shaw, 2008). Difficulty with communication can negatively impact relationships with the hearing-impaired person’s significant others, and in family life in general (Tye-Murray, 2009). Furthermore, adults living with hearing impairment have higher reported levels of depression, anxiety, interpersonal sensitivity, and hostility (Monzani et al, 2008). A longitudinal study of over 12 000 adults in Canada found health-related quality of life measures identified hearing
Correspondence: Rebecca Kelly-Campbell, Department of Communication Disorders, University of Canterbury, Private Bag 4800, Christchurch, 8140, New Zealand. E-mail: [email protected] (Received 16 May 2014; accepted 20 October 2014 ) ISSN 1499-2027 print/ISSN 1708-8186 online © 2015 British Society of Audiology, International Society of Audiology, and Nordic Audiological Society DOI: 10.3109/14992027.2014.979952
HA & HAT in NZ
Abbreviations BEPTA HHIA HHIE MCS PCS QuickSIN SF-36 WEPTA
Better ear pure-tone average Hearing handicap inventory for adults Hearing handicap inventory for the elderly Mental component scale Physical component scale Quick speech in noise test Medical Outcomes Study 36-item short-form health survey Worse ear pure-tone average
deficit to be one of two statistically significant predictors of risk of mortality (Feeny et al, 2012). The most common audiologic rehabilitation approach to address adult-onset hearing impairment is the provision of hearing aids (Boothroyd, 2007). A systematic review of the literature on hearing-aid benefits for adults concluded that interventions for hearing impairment can improve a person’s perception of quality of life (Chisolm et al, 2007). The benefit of hearing aids on quality of life is clear and robust when measured with disease-specific health-related quality of life instruments (Chisolm et al, 2007). This benefit has been shown to be sustained for at least one year after baseline in the social, emotional, and communication domains following intervention with hearing aids (Chisolm et al, 2004; Mulrow et al, 1992). Although hearing aids have also been associated with improvement on generic health-related quality of life measures (Joore et al, 2002), particularly the Physical Component Scale of the Short-form 36 (Chia et al, 2007), the evidence has not been strong enough to support a conclusion when effect sizes for within subject effects are taken into account (Chisolm et al, 2007). Use of hearing aids has also been correlated with reduction in measures of depression (Acar et al, 2011; Boi et al, 2012; Cacciatore et al, 1999; Goorabi et al, 2008; Metselaar et al, 2009; Mulrow et al, 1990). Two studies in particular (Jerger et al, 1996; Yueh et al, 2011) have focused on hearing assistance technology as separate from hearing aids within a population of study participants, looking at the impact of hearing assistance technology adoption on health-related quality of life; to date there is no conclusive evidence that hearing assistance technology usage has a positive impact on health-related quality of life measures, particularly with respect to the report of handicap. However, there is a wide range of hearing assistance technology devices available for use, and more research is needed to establish whether or not there are relationships between use of any type of hearing assistance technology and both generic and disease-specific health-related quality of life. Despite research that supports the effectiveness of hearing aids, research has consistently shown that adults with acknowledged hearing impairment do not routinely own or use hearing aids. The 2012 MarkeTrak report reiterated that 25% of adults in the United States who report hearing impairment own hearing aids (Kochkin, 2012). This adoption rate varies by degree of hearing impairment, with more self-perceived hearing impairment being related to higher adoption rates. This rate is also positively related to age: the older a person is, the more likely that person is to adopt hearing aids. The 2012 EuroTrak UK survey report indicated that in the United Kingdom, 42.2% of adults with hearing impairment own hearing aids (EHIMA). Like the US MarkeTrak report, the EuroTrak UK
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report found that the hearing-aid adoption rate is positively related to self-perceived degree of hearing impairment. Of the adults who own hearing aids, not all of them choose to use them consistently. In 2010, MarkeTrak VIII researchers reported that 12.4% of hearingaid owners do not use their aids at all (Kochkin et al, 2010). In the UK, 29% of adults use their hearing aids between 1 and 4 hours a day (EHIMA, 2012). In New Zealand, it is estimated that 46% of adults (persons aged 15 years and older) with disabling hearing impairment use equipment to meet their hearing needs (Office for Disability Issues and Statistics New Zealand, 2013). This equipment includes both hearing aids and hearing assistance technology such as amplified telephones and captioned television. Greville (2005) reported that 28% of adults with a hearing impairment use hearing aids, 10% use amplified telephones, 3% use teletext/television captioning, 1% use loop, FM, or infra-red systems, and 1% use computers to communicate. Similar to findings from overseas, the likelihood of using hearing aids among adults in New Zealand increases with age: only 5% of 25–44 year olds with hearing impairment use hearing aids compared with 63% of adults aged 85 years and older. Jerram and Purdy (2001) reported on a sample of hearing-impaired adults in New Zealand and found the results to be comparable to contemporary studies overseas. In that study, 26% of participants used their hearing aids between one and four hours per day, which is consistent with the EuroTrak UK 2012 data. Specifically, Jerram and Purdy found participants had positive expectations of hearing aids, experienced a wide range of attitudes towards hearing-aid use, high levels of satisfaction, and more benefit in difficult listening situations. This study focused on two questions. (1) What are the factors that differentiate adults with hearing impairment living in New Zealand based on hearing aid use? (2) What are the factors that differentiate adults with hearing impairment living in New Zealand based on hearing assistance technology use? Demographic, audiometric, and health-related quality of life variables were used to measure potential factors.
Methods Participants Before commencing participant recruitment, required sample size was determined using a priori sample size analysis. The level of statistical significance was set at .05 and statistical power at .80. An effect size of d ⫽ .50, that is at least a moderate effect (Cohen, 1977), was used to define clinical meaningfulness. It was determined that 42 participants in each comparison group were required for this study. This study received approval from the University of Canterbury Human Ethics Committee prior to the commencement of participant recruitment. Participants were recruited throughout New Zealand. Recruiting methods included: newsprint media, radio media, other print media (e.g. flyers, posters), electronic media (e.g. newsletters, email lists) and word of mouth. Eligibility of those expressing interest was assessed using the following inclusion criteria: 1. 2. 3. 4.
Over the age of 18 Have verified or verifiable hearing impairment Ability to use spoken English for communication Ability to complete the information sheet and self-assessment questionnaires 5. Ability to return questionnaires to the researchers.
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Procedures Upon enrolling in the study, participants were provided with a packet that contained: (1) Demographic questionnaire, (2) Hearing handicap inventory for adults or hearing handicap inventory for the elderly as age-appropriate, (3) Medical outcomes study 36-item shortform health survey, (4) Postage paid return envelope. Participants who had a hearing test within the previous 18 months were asked to include a copy of their hearing test when returning the packet. Participants who did not have a recent hearing test were provided with one at no cost to them. Participants were invited to obtain their hearing test at the University of Canterbury Hearing Clinic if they lived conveniently close. Otherwise, participants were directed to their nearest participating audiology clinic and the University was invoiced for their hearing test. Participants who were required to obtain a hearing test were reimbursed with a $20 voucher to cover the cost of travel.
Measures Demographic information was obtained via a questionnaire. Participants were asked in an open-ended question if they owned hearing aids, and if so, how often they used them. Regular hearing-aid use was defined as a response that indicated hearing aids were worn most of the time, during waking hours, on a regular basis, etc. Similarly, participants were asked if they used any assistance technology, and if so, what they used. Participants were asked to list all the assistance devices they used. Audiometric information included pure-tone air and bone conduction thresholds, speech understanding in both quiet and noise. Pure-tone air conduction thresholds were quantified via two measures. The better hearing ear pure-tone average (BEPTA) represented the average air-conduction thresholds at 0.5, 1, 2, and 4 kHz for the better hearing ear. The worse hearing ear pure-tone average (WEPTA) represented the average air-conduction thresholds at 0.5, 1, 2, and 4 kHz for the worse hearing ear. The speech in noise test used for this study was the quick speech in noise test (QuickSIN) (Etymotic Research, 2001; Killion et al, 2004). Generic health-related quality of life was measured with the Medical Outcomes Study 36-item short-form health survey (SF-36) (Ware & Sherbourne, 1992). The SF-36 does not measure the effects of hearing impairment on an individual’s life, but rather, aims to measure overall perception of health-related quality of life. The SF-36 consists of two component scales: a physical component scale (PCS), which provides four subscale scores on components of physical health, bodily pain, role limitations due to physical health problems, and general health perceptions; and a mental component scale (MCS), which provides four further subscale scores on components of mental health, vitality, role limitations due to mental health problems, and social functioning (Abrams & Chisolm, 2007). Responses on each of the subscales can range in score from 0–100, corresponding with lowest physical or mental function to highest. The means scores for all subscales are standardized to 50, with a standard deviation of 10 (Abrams et al, 2005). Studies have shown that perception of health-related quality of life is negatively impacted by hearing impairment (Dalton et al, 2003; Hickson et al, 2008; Mulrow et al, 1990). Previous research in the non-hearing impaired population has shown that some demographic variables may impact perception of generic and disease-specific health-related quality of life. Data from international studies and from New Zealand Ministry of Health - Manatu¯ Hauora and Statistics New Zealand - Tatauranga Aotearoa have shown that scores on
both the PCS and MCS of the SF-36 are affected by age (Butterworth & Crosier, 2004; Hopman et al, 2000; Ministry of Health - Manatu¯ Hauora, 1999), income (Ministry of Health - Manatu¯ Hauora, 1999), sex (Statistics New Zealand - Tatauranga Aotearoa, 2013), and level of education (Ministry of Health - Manatu¯ Hauora, 1999). Disease-specific health-related quality of life was measured with the hearing handicap inventory for adults (HHIA) (Newman et al, 1991) for participants under the age of 65 years, and with the hearing handicap inventory for the elderly (HHIE) (Ventry & Weinstein, 1982) for participants 65 years of age and older. These two questionnaires will be collectively referred to as the “HHI”. The HHI measures the perceived psychosocial effects of hearing impairment on specific areas of a person’s life. The HHIE was developed to be used with non-institutionalized subjects aged 65 and over. The HHIA, which incorporates occupational and leisure questions, was developed for use with working adults under age 65. The HHIE and HHIA have high levels of internal consistency and test-retest reliability (0.95) and validity (0.89) (Newman et al, 1991; Weinstein et al, 1986). Both the HHIE and HHIA consist of 25 questions, which are comprised of two subscales. The emotional subscale consists of 13 questions which address the impact of hearing loss on the emotional domain of a person’s life. The second subscale, which addresses the perceived impact of hearing loss on function in social situations, consists of 12 questions. A “yes” response to any of the 25 items adds four points towards the total score, a “sometimes” adds two points, and a “no” adds zero points, for a maximum total of 100 points (Ventry & Weinstein, 1982). Participants who wore hearing aids and/or used hearing assistance technology devices were asked to complete the HHI in the unaided condition (i.e. as they are when they are not using their devices).
Results Participant summary Complete datasets were obtained from 123 participants. Many clinics in New Zealand do not routinely measure the ability to understand speech in noise and some participants had hearing impairment too great to measure supra-threshold speech understanding. Therefore, QuickSIN results were obtained for 64 participants. While the demographic questionnaire was completed by all study participants, only 92 participants reported any income. There were 53 males in this study and 70 females. The majority of participants (N ⫽ 84) listed “New Zealander” as their ancestry, 34 participants listed their ancestry as either European or North American, and five participants listed their ancestry as Ma¯ ori. Of the 123 participants who completed the study, 73 reported using at least one hearing aid on a regular basis and 50 reported not using a hearing aid on a regular basis. Of the 50 non-hearing aid users, eight reported owning at least one hearing aid but not using it on a regular basis. All of the participants who owned hearing aids (current and former users, N ⫽ 81) also reported using at least one type of hearing assistance technology device. The types of hearing assistance technology participants reported using are shown in Table 1. The 42 participants who reported never owning hearing aids also reported not using hearing assistance technology. Descriptive statistics for the study participants are shown in Table 2 and Table 3. The demographic characteristics of the population sampled in this study were not representative of the general population of NZ in terms of the following variables: the income and education level of this sample were higher than the national averages, and
HA & HAT in NZ Table 1. Hearing assistance technology used by the study participants (N ⫽ 81).
Telephone
TV/Radio
Public Alerting
Type of assistance
Number of participants
Special/amplified telephone Speaker telephone CapTel Relay/TTY Telecoil Headphones Closed captions Bluetooth Loop system FM system Device Sound dog
63 12 12 4 4 19 12 4 9 6 4 1
Note: Some participants reported using more than one type of hearing assistance technology.
the ancestry of this population reflected an under-representation of people with Ma¯ ori ancestry (Statistics New Zealand - Tatauranga Aotearoa, 2013). There was a higher proportion of females compared with males in this study in relation to the overall population in New Zealand and the hearing-impaired population. In addition, while participants lived on both the North Island and the South Island, the proportion of participants in this study living on the South Island was not reflective of the demographic trends in New Zealand (with the majority of residents living on the North Island).
Hearing-aid ownership and use One-way analysis of variance (ANOVA) and chi-square tests were performed to determine if any demographic, audiometric, and quality of life variables were significantly different between the groups based on hearing-aid use. Results of the ANOVA and Cohen’s d effect sizes for each comparison are shown in Table 2. There were no significant differences between the groups based on any demographic variable or the generic health-related quality of life questionnaire (SF-36). There were significant differences between the groups based on audiometric data and the disease-specific health-related quality of life questionnaire (HHI). Specifically, hearing-aid users had more difficulty understanding speech in background noise, had poorer hearing in their both their better and worse hearing ears, and perceived more consequences of hearing impairment in their everyday lives (both emotionally and socially) than non-hearing aid users. That is, current hearingaid users had poorer objective audiometric measures and subjective perceptions than participants who do not use hearing aids. All of the statistically significant findings had Cohen’s d effect sizes greater than .50 (moderate size) and were considered statistically significant and likely to be clinically meaningful. A discriminant analysis was performed to determine the significant variables that best classified the participants in terms of hearing-aid use. Box’s test of equality of covariance matrices was non-significant, so the assumption was not violated. A step-wise method was used and two variables were entered into the equation: HHI social and BEPTA. The discriminant equation is as follows: Di ⫽ ⫺ 7.97 ⫹ .303 (Social) ⫹ .107 (BEPTA). Using this equation, 80.5% of the original cases
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Table 2. Descriptive statistics, results of ANOVA F-test, and Cohen’s d effect sizes for hearing-aid users and non-users.
Age (years) Current HA user Non-HA user Hours worked (/week) Current HA user Non-HA user Income ($1000) Current HA user Non-HA user SNR loss (dB) Current HA user Non-HA user BEPTA (dB HL) Current HA user Non-HA user WEPTA (dB HL) Current HA user Non-HA user HHI emotional Current HA user Non-HA user HHI social Current HA user Non-HA user MCS Current HA user Non-HA user PCS Current HA user Non-HA user
Mean
Standard deviation
64.9 61.9
12.4 13.3
13.0 12.8
17.2 16.1
37.4 38.8
25.0 20.6
10.1 4.6
7.3 3.7
14.6
⬍ .001
51.6 26.1
24.3 18.8
39.2
⬍ .001
63.8 44.7
22.9 26.2
18.4
⬍ .001
.77
30.8 22.7
10.9 13.3
13.8
⬍ .001
.67
31.2 20.6
9.3 10.4
34.8
⬍ .001
72.2 70.2
19.1 19.8
.33
.56
.10
72.2 73.1
19.1 20.6
.06
.80
.04
F
p
1.7
d
.19
.23
.005
.945
.01
.07
.78
.04
.68
1.1
1.1
Current HA user ⫽ participants reporting regular use of hearing aids (N ⫽ 73). Non-HA user ⫽ participants reporting not using hearing aids on a regular basis (N ⫽ 50). SNR loss ⫽ signal-to-noise ratio loss as measured by the QuickSIN test. BEPTA ⫽ average air conduction thresholds at 0.5, 1, 2, and 4 kHz for the better hearing ear. WEPTA ⫽ average air conduction thresholds at 0.5, 1, 2, and 4 kHz for the worse hearing ear. HHI ⫽ Hearing handicap inventory. MCS ⫽ Mental component scale of the SF-36 questionnaire. PCS ⫽ Physical component scale of the SF-36 questionnaire.
were correctly classified and 78.9% of the cross validated cases were correctly classified. Cross validation is a process of assessing the accuracy of a model. If the proportion of the cross validated cases correctly classified exceeds the proportional by chance accuracy, the discriminant ability of the model is supported. In this case, the proportional by chance accuracy was calculated to be 50.2%. Thus, the discriminant ability of this model is supported.
Hearing assistance technology use Participants who reported using hearing assistance technology reported a wide variety of assistance options and many reported using more than one option. The most commonly used technology involved assistance using the telephone, with 79 hearing assistance technology users reporting using one or more devices. The next most common listening issue involved the television and/or radio. A total of 31 participants reported using a device to assist in listening in these situations. Fifteen participants reported using assistance tech-
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Table 3. Descriptive statistics, results of ANOVA F-test, and Cohen’s d effect sizes for hearing assistance technology users and non-users.
Age (years) HAT user HAT non-user Hours worked (/week) HAT user HAT non-user Income ($1000) HAT user HAT non-user SNR loss (dB) HAT user HAT non-user BEPTA (dB HL) HAT user HAT non-user WEPTA (dB HL) HAT user HAT non-user HHI Emotional HAT user HAT non-user HHI Social HAT user HAT non-user MCS HAT user HAT non-user PCS HAT user HAT non-user
Mean
Standard deviation
64.7 61.7
12.5 13.3
12.4 14.0
16.6 16.9
37.1 39.8
25.0 19.8
9.6 4.0
6.8 3.5
16.7
⬍ .001
50.2 23.8
23.9 18.3
39.1
⬍ .001
64.4 40.0
22.5 24.9
30.0
⬍ .001
.98
31.1 20.9
11.2 12.5
21.2
⬍ .001
.83
30.9 19.1
9.4 9.8
43.2
⬍ .001
71.8 70.6
19.6 18.8
.09
.76
.05
72.7 72.3
19.5 20.4
.01
.91
.01
F
p
d
1.5
.22
.22
.25
.61
.09
.29
.58
.09
.73
impairment in their everyday lives (both emotionally and socially) than non-hearing assistance technology users. All of the statistically significant findings had Cohen’s d effect sizes greater than .50, that is a moderate effect size, and were considered statistically significant and likely to be clinically meaningful. A discriminant analysis was performed to determine the significant variables that best classified the participants in terms of hearing assistance technology use. Box’s test of equality of covariance matrices was non-significant, so the assumption was not violated. A step-wise method was used and two variables were entered into the equation: HHI social and WEPTA. The discriminant equation is as follows: Di ⫽ ⫺ 3.67 ⫹ .092 (Social) ⫹ .03 (WEPTA). Using this equation, 81.3% of the original cases were correctly classified and 78.9% of the cross validated cases were correctly classified. The proportional by chance accuracy was calculated to be 37.9%. Thus, the discriminant ability of this model is supported.
Discussion 1.1
1.2
HAT user ⫽ participants reporting using at least one type of hearing assistance technology device (N ⫽ 81). HAT non-user ⫽ participants reporting not using any hearing assistance technology (N ⫽ 42). SNR loss ⫽ signal-to-noise ratio loss as measured by the QuickSIN test. BEPTA ⫽ average air conduction thresholds at 0.5, 1, 2, and 4 kHz for the better hearing ear. WEPTA ⫽ average air conduction thresholds at 0.5, 1, 2, and 4 kHz for the worse hearing ear. HHI ⫽ Hearing handicap inventory. MCS ⫽ Mental component scale of the SF36 questionnaire. PCS ⫽ Physical component scale of the SF-36 questionnaire.
nology in public places. Finally, four participants reported using an alerting device and one reported using a sound dog (understood by clinicians and researchers in the field). One-way analysis of variance (ANOVA) and chi-square tests were performed to determine if any demographic, audiometric, and quality of life variables were significantly different between the groups based on hearing assistance technology use. Results of the ANOVA and Cohen’s d effect sizes for each comparison are shown in Table 3. Similar to the previous analysis, there were no significant differences between the groups, based on any demographic variable, nor on the generic health-related quality of life questionnaire (SF-36). There were significant differences between the groups based on audiometric data and the disease-specific health-related quality of life questionnaire (HHI). As in the previous analysis, hearing assistance technology users had more difficulty understanding speech in background noise, had poorer hearing in their both their better and worse hearing ears, and perceived more consequences of hearing
Results of this study showed that participants did not differ in terms of demographic variables or generic health-related quality of life when classified by either hearing-aid use or hearing assistance technology use. The relationship between demographic variables and hearing-aid use is complex, and this complexity is reflected in the mixed data reported in various studies. Demographic factors such as older age, female sex, higher satisfaction with income, a family history of hearing impairment, and higher education level have been shown to have a positive relationship with ownership of hearing aids (Garstecki & Erler, 1998; Gussekloo et al, 2003; Kochkin, 1993, 2007, 2009), though not all data are supportive of these relationships (Gussekloo et al, 2003; Helvik et al, 2008). Participants in this study reported a higher income and level of education than the general New Zealand population; therefore the lack of trend present in this study may not be repeatable were a sample more reflective of the New Zealand population surveyed. Information regarding satisfaction with income, and family history of hearing impairment were not collected in this study. Participants in this study who used hearing devices reported more consequences of hearing impairment than non-device users. It is important to recall that participants were asked to complete the HHI as they function without any hearing device. Therefore the differences between the groups reflect participants’ perceptions about the underlying impact of their hearing impairment rather than the impact of hearing devices. The results of the discriminant analyses were similar for the classification of participants based on hearingaid use and on hearing assistance technology use. In both cases, the variable that best classified the participants was the social scale of the HHI. That is, it was the perceived social consequences of hearing impairment that best differentiated device users from non-users. Swan and Gatehouse (1990) argue that it is the consequences of hearing impairment on a person’s everyday life that prompts help-seeking behaviour. This notion has been supported by other researchers. Humes and colleagues (2003) controlled for gender and degree of hearing impairment and found only non-audiologic factors differentiated their groups of hearing-aid users. Gussekloo et al (2003) found mean hearing disability score was higher for those who accepted intervention than for those who rejected it. The second best classifying variable in both analyses related to hearing sensitivity. For the hearing-aid use classification, it was the better hearing ear while for the hearing assistance technology use classification, it was the worse hearing ear. Thus, device users
HA & HAT in NZ exhibited poorer hearing than non-device users. Researchers have consistently found that a perception of worsening hearing is one of the factors related to help-seeking behaviour and hearing-aid ownership (Helvik et al, 2008; Kochkin, 2009). These findings may be related to the sex (Garstecki & Erler, 1998) and age (Gusselkoo et al, 2003) of the participants. Arguably, hearing-aid ownership is not solely related to degree of hearing impairment. Other influential variables to consider are social support, perception of hearing handicap, dexterity, activity limitation, and participation restriction (Cox et al, 2005; Fischer et al, 2011; Garstecki & Erler, 1998; Gopinath et al, 2011; Helvik et al, 2008; Humes et al, 2003). Participants in this study who used hearing devices also exhibited more difficulty understanding speech in background noise than non-device users. This finding also supports previous literature (Walden & Walden, 2004). Robertson and colleagues (2012) examined variables that differentiated adults based on hearing-aid purchase decision. The groups were not significantly different in terms of demographic variables, degree of hearing impairment or ability to understand speech in quiet settings. However, they were significantly different in terms of their ability to understand speech in noise. Specifically, participants who chose to purchase hearing aids and keep them had significantly poorer SNR loss than participants who chose to return purchased hearing aids and those who chose not to purchase them. There is very little literature available with which to compare the results of the hearing assistance technology analysis, which highlights the need for additional research in this area. The similar results of the two discriminant analyses may reflect similarities in decision making for both hearing-aid and hearing assistance technology users. While data exploring predictive variables for hearing assistance technology ownership and use are lacking, the findings in this study show, overall, that distinguishing variables for both hearing assistance technology and hearing-aid users are similar for this sample. It is interesting to note that the most common hearing assistance technology reported by Greville (2005) was amplified telephones and that remains the most common assistance technology used in this sample. Participants were recruited into this study in an attempt to obtain a diverse group of adults with hearing impairment living in New Zealand that would be representative of the population. Demographically, the participants in the study did not resemble the New Zealand population in terms of income, education, sex ratio, and ancestry. In addition, a high proportion of participants lived on the South Island, which is in contrast to the demographics of New Zealand. According to the 2012 Census (Statistics New Zealand - Tatauranga Aotearoa, 2013), approximately 3.4 million people lived on the North Island, and approximately 1 million people lived on the South Island. This sampling did not achieve a true representative sample and the results of this study therefore lack some generalizability to all adults with hearing impairment living in New Zealand. Further research needs to be conducted in which participants more closely resemble the demographics of the New Zealand population. Other limitations of this study need to be considered. The study design was descriptive in nature and causal relationships between variables cannot be assumed. Another limitation of this study is the inability of the results to indicate precisely how the participants feel about the impact of hearing impairment on their lives. Just as severity of hearing impairment does not necessarily determine the extent to which one’s communication and lifestyle are impacted by hearing impairment, it is beyond the scope of health-related quality of life instruments to expand upon the meaning of the results for the
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individual participants. That is, two individuals could have the same score on one of the health-related quality of life questionnaires used in this study, yet feel quite differently about the impact of hearing impairment upon their lives. Further research into the impact of hearing impairment on perception of health-related quality of life might include open-ended questions conducted in interview or written format. Finally, only eight study participants were former hearing-aid users and therefore analyses could not be performed on this group. More research is needed to better understand factors that are related to hearing-aid use and disuse amongst hearing-aid owners. The results of this study have potential implications for clinicians working in Aotearoa/ New Zealand. Specifically, there are four clinical suggestions that follow from these findings. First, given that the demographic variables did not discriminate device users and nonusers, clinicians are encouraged not to rely on variables such as age, gender, and income when making hearing-aid and assistive technology recommendations. Second, including disease-specific health-related quality of life measures such as the HHI in a clinical evaluation can give clinicians additional meaningful information about the impact of hearing impairment for the people they serve. Clinicians may use the information from questionnaires such as the HHI to help make device recommendations that are specifically targeted at the quality of life issues identified. Third, the results of this study also suggest clinicians would gain valuable information by employing such tools as a speech understanding in noise test alongside their pure-tone and speech audiometry because SNR loss was a variable that was found to be statistically significantly different between device users and non-users. This finding supports previous literature in regards to the positive relationship between SNR loss and hearing aid ownership (Robertson et al, 2012; Walden & Walden, 2004). Use of such tools can help validate the experience of the individual with hearing impairment and can help identify specific technology to address the problems encountered understanding speech in noise (e.g. use of directional microphones, FM, or loop systems). Finally, the results of this study suggest that adults with hearing impairment in New Zealand who use hearing aids also use hearing assistance technology. The overlap of use between these two types of devices has important clinical implications in New Zealand. Provision of hearing aids falls within the purview of audiologists and audiometrists. Provision of hearing assistance technology tends to fall within the purview of hearing therapists. It is important that these professionals work closely with each other to ensure continuity of service for hearing impaired people in New Zealand.
Conclusion In conclusion, device users (hearing aid and hearing assistance technology) were not significantly different in terms of demographic variables than non-device users. The groups were also not significantly different in terms of generic health-related quality of life, as measured by the SF-36 questionnaire. However, participants who reported using hearing aids exhibited significantly more difficulty understanding speech in background noise and significantly poorer hearing than participants who reported not using hearing aids. In addition, participants who reported using hearing aids reported poorer disease-specific quality of life (in the unaided condition) as measured by the HHI than those who reported not using hearing aids. Similar results were found for participants who reported using hearing assistance technology. These participants reported more difficulty understanding speech in background noise, significantly
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poorer hearing, and reduced disease-specific quality of life compared with participants who did not report using hearing assistance technology.
Acknowledgements We would like to acknowledge Dr Donal Sinex for his assistance with this project and in preparing this manuscript. Declaration of interest: The authors report no conflicts of interest.
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Gopinath B., Schneider J., Hartley D., Teber E., McMahon C. et al. 2011. Incidence and predictors of hearing aid use and ownership among older adults with hearing loss. Ann Epidemiol, 21, 497–506. Greville A. 2005. Hearing impaired and deaf people in New Zealand: An update on population numbers and characteristics. Auckland: Greville Consulting. Gussekloo J., de Bont L., von Faber M., Eekhof J., de Laat J. et al. 2003. Auditory rehabilitation of older people from the general population: The Leiden 85-plus study. Br J Gen Pract, 53, 536–540. Helvik A., Wennberg S., Jacobson G.P. & Hallberg L.R. 2008. Why do some individuals with objectively verified hearing loss reject hearing aids? Audiological Medicine, 6, 141–148. Hickson L., Allen J., Beswick R., Fulton M., Wolf D. et al. 2008. Relationships between hearing disability, quality of life and wellbeing in older community-based Australians. Australian and New Zealand Journal of Audiology, 30, 99–112. Hopman W.M., Towheed T., Anastassiades T., Tenenhouse A., Poliquin S. et al. 2000. Canadian normative data for the SF-36 health survey. Canadian Medical Association Journal, 163, 265–271. Humes L., Wilson D. & Humes A. 2003. Examination of differences between successful and unsuccessful elderly hearing aid candidates matched for age, hearing loss and gender. Int J Audiol, 42, 432–441. Jennings M.B. & Shaw L. 2008. Impact of hearing loss in the workplace: Raising questions about partnerships with professionals. Work (Reading, USA), 30, 289–295. Jerger J., Chmiel R., Floirn E., Pirozzolo F. & Wilson N. 1996. Comparison of conventional amplification and an assistive listening device in elderly persons. Ear Hear, 17, 490–504. Jerram J.C. & Purdy S.C. 2001. Technology, expectations, and adjustment to hearing loss: Predictors of hearing aid outcome. J Am Acad Audiol, 12, 64–79. Joore M.A., Potjewid J., Timmerman A.A. & Anteunis L.J.C. 2002. Response shift in the measurement of quality of life in hearing impaired adults after hearing aid fitting. Qual Life Res, 11, 299–307. Keller B.K., Morton J.L., Thomas V.S. & Potter J.F. 1999. The effect of visual and hearing impairments on functional status. J Am Geriatr Soc, 47, 1319–1325. Kelly-Campbell R.J. & Atcherson S.R. 2012. Perception of quality of life for adults with hearing impairment in the LGBT community. J Comm Disord, 45, 367–377. Killion M.C., Niquette P.A., Gudmundsen G.I., Revit L.J. & Banerjee S. 2004. Development of a quick speech-in-noise test for measuring signal to noise ratio loss in normal-hearing and hearing-impaired listeners. J Acoust Soc Am, 116, 2395–2405. Kochkin S. 1993. MarkeTrak III: Why 20 million in US don’t use hearing aids for their hearing loss. Hearing Journal, 46, 28–31. Kochkin S. 2007. MarkeTrak VIII: 25-year trends in the hearing health market. Hearing Journal, 60, 24–50. Kochkin S. 2009. MarkeTrak VIII: 25-year trends in the hearing health market. Hearing loss population now at 34.25 million Americans. Hearing Review, October, 12–31. Hearing Review, 16, 12–31. Kochkin S. 2012. MarkeTrak VIII: The key influencing factors in hearing aid purchase intent. Hearing Review, 19, 12–25. Kochkin S., Beck D.L., Christensen L.A., Compton-Conley C., Fligor B.J. et al. 2010. MarkeTrak VIII: The impact of the hearing healthcare professional on hearing aid user sucess. Hearing Review, 17, 12–34. Metselaar M., Maat B., Krijnen P., Verschuure H., Dreschler W. et al. 2009. Self-reported disability and handicap after hearing-aid fitting and benefit of hearing aids: Comparison of fitting procedures, degree of hearing loss, experience with hearing aids and uni- and bilateral fittings. European Archives of Oto-Rhino-Laryngology, 266, 907–917. Ministry of Health - Manat Hauora. 1999. Taking the Pulse: The 1996/97 New Zealand health survey: SF-36 data analysis. Retrieved from http:// www.health.govt.nz/publication/taking-pulse-1996-97-new-zealandhealth-survey-sf-36-data-analysis Monzani D., Galeazzi G.M., Genovese E., Marrara A. & Martini A. 2008. Psychological profile and social behaviour of working adults with mild or moderate hearing loss. Acta Otorhinolaryngologica Italica, 28, 61–11.
HA & HAT in NZ Mulrow C.D., Aguilar C., Endicott J.E., Velez R., Tuley M.R. et al. 1990. Association between hearing impairment and quality of life of older individuals. J Am Geriatr Soc, 38, 45–50. Mulrow C.D., Tuley M.R. & Aguilar C. 1992. Sustained benefits of hearing aids. J Sp Lang Hear Res, 35, 1402–1405. National Foundation for the Deaf. from http://www.nfd.org Newman C.W., Weinstein B.E., Jacobson G.P. & Hug G.A. 1991. Test-retest reliability of the Hearing Handicap Inventory for Adults. Ear Hear, 12, 355–357. Office for Disability Issues and Statistics New Zealand. 2013. Disability and formal supports in New Zealand in 2006: Results from the 2006 Disability Survey. Retrieved from http://www.stats.govt.nz Robertson M., Kelly-Campbell R.J. & Wark D. 2012. Use of audiometric variables to differentiate groups of adults based on hearing aid ownership and use. Contemporary Issues in Communication Science and Disorders, 39, 114–120. Statistics New Zealand - Tatauranga Aotearoa. 2013. 2013 Census. Retrieved from http://www.stats.govt.nz/Census/2013-census.aspx Strawbridge W.J., Wallhagen M.I., Shema S.J. & Kaplan G.A. 2000. Negative consequences of hearing impairment in old age: A longitudinal analysis. Gerontologist, 40, 320–326.
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Swan I. & Gatehouse S. 1990. Factors influencing consultation for management of hearing disability. British Journal of Audiology, 24, 155–160. Thorne P.R., Ameratunga S.N., Stewart J., Reid N., Williams W. et al. 2008. Epidemiology of noise-induced hearing loss in New Zealand. New Zealand Medical Journal, 121, 33–44. Tye-Murray N. 2009. Foundations of Aural Rehabilitation: Children, Adults, and Their Families. Clifton Park, USA: Delmar Cengage Learning. Ventry I.M. & Weinstein B.E. 1982. The Hearing Handicap Inventory for the Elderly: A new tool. Ear Hear, 3, 128–133. Walden T.C. & Walden B.E. 2004. Predicting success with hearing aids in everyday living. J Am Acad Audiol, 15, 342–352. Ware J.E. & Sherbourne C.D. 1992. The MOS 36-item short form health survey (SF-36): I. Conceptual framework and item selection. Medical Care, 30, 473–483. Weinstein B.E., Spitzer J.B. & Ventry I.M. 1986. Test-retest reliability of the Hearing Handicap Inventory for the Elderly. Ear Hear, 7, 295–299. Yueh B., Souza P., McDowell J., Collins M., Loovis C. et al. 2011. Randomized trial of amplification strategies. Arch Otolaryngol Head Neck Surg, 127, 1197–1204.
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Original Article
Hearing aid and hearing assistance technology use in Aotearoa/New Zealand Rebecca J. Kelly-Campbell & Kamea Lessoway Department of Communication Disorders, University of Canterbury, Christchurch, New Zealand
Abstract Objective: The purpose of this study was to describe factors that are related to hearing aid and hearing assistance technology ownership and use in Aotearoa/New Zealand. Design: Adults with hearing impairment living in New Zealand were surveyed regarding health-related quality of life and device usage. Audiometric data (hearing sensitivity and speech in noise) were collected. Study sample: Data were obtained from 123 adults with hearing impairment: 73 reported current hearing-aid use, 81 reported current hearing assistance technology use. Results: In both analyses, device users had more difficulty understanding speech in background noise, had poor hearing in both their better and worse hearing ears, and perceived more consequences of hearing impairment in their everyday lives (both emotionally and socially) than non-hearing-aid users. Discriminant analyses showed that the social consequences of hearing impairment and the better ear hearing best classified hearing aid users from non-users but social consequences and worse ear hearing best classified hearing assistance technology users from non-users. Conclusions: Quality of life measurements and speech-in-noise assessments provide useful clinical information. Hearing-impaired adults in New Zealand who use hearing aids also tend to use hearing assistance technology, which has important clinical implications.
Key Words: Hearing aids; hearing assistance technology; speech in noise; New Zealand; hearing assistive devices It is estimated that one in six New Zealanders experiences hearing impairment (National Foundation for the Deaf). The most detailed and recent prevalence data regarding hearing impairment and hearing-aid use in New Zealand (“Aotearoa” in te reo Ma¯ ori) was a population survey associated with the 2001 census (Greville, 2005). This survey reports that the prevalence of hearing impairment in New Zealand is approximately 10.3%. When considering the entire hearing-impaired population of New Zealand, 8% comprise children under the age of 14 years, while approximately 33% of hearing-impaired people in New Zealand are adults between the ages of 45 and 64 years. There is a sex disparity in the prevalence of hearing impairment in New Zealand: the overall male to female ratio of people with hearing impairment is 1.37:1.0. It is estimated that between 30% and 50% of the prevalence of hearing impairment in New Zealand can be attributed to noise exposure (Thorne et al, 2008). According to Greville (2005), the prevalence of hearing impairment for people aged 65 years and older of New Zealand Ma¯ ori ancestry is 24.4% while the prevalence of hearing impairment for people aged 65 years and older of non-Ma¯ ori ancestry is 22.0%. Finally, there is an income disparity in New Zealand between adults
with a hearing impairment and the total adult population. In 2001, 67% of adults with hearing impairment had personal incomes below $20 000, compared with 52% of the total adult population (Greville, 2005). The negative psychosocial consequences for adults living with hearing impairment are varied, and have been well documented in the literature internationally. Amongst the more common consequences of hearing impairment are difficulties with communication, social and emotional isolation, greater dysfunction for physical and mental health, and a negative impact on perception of overall quality of life (Chia et al, 2007; Dalton et al, 2003; Keller et al, 1999; Mulrow et al, 1990; Strawbridge et al, 2000). Hearing impairment can also have negative consequences in the workforce (Jennings & Shaw, 2008). Difficulty with communication can negatively impact relationships with the hearing-impaired person’s significant others, and in family life in general (Tye-Murray, 2009). Furthermore, adults living with hearing impairment have higher reported levels of depression, anxiety, interpersonal sensitivity, and hostility (Monzani et al, 2008). A longitudinal study of over 12 000 adults in Canada found health-related quality of life measures identified hearing
Correspondence: Rebecca Kelly-Campbell, Department of Communication Disorders, University of Canterbury, Private Bag 4800, Christchurch, 8140, New Zealand. E-mail: [email protected] (Received 16 May 2014; accepted 20 October 2014 ) ISSN 1499-2027 print/ISSN 1708-8186 online © 2015 British Society of Audiology, International Society of Audiology, and Nordic Audiological Society DOI: 10.3109/14992027.2014.979952
HA & HAT in NZ
Abbreviations BEPTA HHIA HHIE MCS PCS QuickSIN SF-36 WEPTA
Better ear pure-tone average Hearing handicap inventory for adults Hearing handicap inventory for the elderly Mental component scale Physical component scale Quick speech in noise test Medical Outcomes Study 36-item short-form health survey Worse ear pure-tone average
deficit to be one of two statistically significant predictors of risk of mortality (Feeny et al, 2012). The most common audiologic rehabilitation approach to address adult-onset hearing impairment is the provision of hearing aids (Boothroyd, 2007). A systematic review of the literature on hearing-aid benefits for adults concluded that interventions for hearing impairment can improve a person’s perception of quality of life (Chisolm et al, 2007). The benefit of hearing aids on quality of life is clear and robust when measured with disease-specific health-related quality of life instruments (Chisolm et al, 2007). This benefit has been shown to be sustained for at least one year after baseline in the social, emotional, and communication domains following intervention with hearing aids (Chisolm et al, 2004; Mulrow et al, 1992). Although hearing aids have also been associated with improvement on generic health-related quality of life measures (Joore et al, 2002), particularly the Physical Component Scale of the Short-form 36 (Chia et al, 2007), the evidence has not been strong enough to support a conclusion when effect sizes for within subject effects are taken into account (Chisolm et al, 2007). Use of hearing aids has also been correlated with reduction in measures of depression (Acar et al, 2011; Boi et al, 2012; Cacciatore et al, 1999; Goorabi et al, 2008; Metselaar et al, 2009; Mulrow et al, 1990). Two studies in particular (Jerger et al, 1996; Yueh et al, 2011) have focused on hearing assistance technology as separate from hearing aids within a population of study participants, looking at the impact of hearing assistance technology adoption on health-related quality of life; to date there is no conclusive evidence that hearing assistance technology usage has a positive impact on health-related quality of life measures, particularly with respect to the report of handicap. However, there is a wide range of hearing assistance technology devices available for use, and more research is needed to establish whether or not there are relationships between use of any type of hearing assistance technology and both generic and disease-specific health-related quality of life. Despite research that supports the effectiveness of hearing aids, research has consistently shown that adults with acknowledged hearing impairment do not routinely own or use hearing aids. The 2012 MarkeTrak report reiterated that 25% of adults in the United States who report hearing impairment own hearing aids (Kochkin, 2012). This adoption rate varies by degree of hearing impairment, with more self-perceived hearing impairment being related to higher adoption rates. This rate is also positively related to age: the older a person is, the more likely that person is to adopt hearing aids. The 2012 EuroTrak UK survey report indicated that in the United Kingdom, 42.2% of adults with hearing impairment own hearing aids (EHIMA). Like the US MarkeTrak report, the EuroTrak UK
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report found that the hearing-aid adoption rate is positively related to self-perceived degree of hearing impairment. Of the adults who own hearing aids, not all of them choose to use them consistently. In 2010, MarkeTrak VIII researchers reported that 12.4% of hearingaid owners do not use their aids at all (Kochkin et al, 2010). In the UK, 29% of adults use their hearing aids between 1 and 4 hours a day (EHIMA, 2012). In New Zealand, it is estimated that 46% of adults (persons aged 15 years and older) with disabling hearing impairment use equipment to meet their hearing needs (Office for Disability Issues and Statistics New Zealand, 2013). This equipment includes both hearing aids and hearing assistance technology such as amplified telephones and captioned television. Greville (2005) reported that 28% of adults with a hearing impairment use hearing aids, 10% use amplified telephones, 3% use teletext/television captioning, 1% use loop, FM, or infra-red systems, and 1% use computers to communicate. Similar to findings from overseas, the likelihood of using hearing aids among adults in New Zealand increases with age: only 5% of 25–44 year olds with hearing impairment use hearing aids compared with 63% of adults aged 85 years and older. Jerram and Purdy (2001) reported on a sample of hearing-impaired adults in New Zealand and found the results to be comparable to contemporary studies overseas. In that study, 26% of participants used their hearing aids between one and four hours per day, which is consistent with the EuroTrak UK 2012 data. Specifically, Jerram and Purdy found participants had positive expectations of hearing aids, experienced a wide range of attitudes towards hearing-aid use, high levels of satisfaction, and more benefit in difficult listening situations. This study focused on two questions. (1) What are the factors that differentiate adults with hearing impairment living in New Zealand based on hearing aid use? (2) What are the factors that differentiate adults with hearing impairment living in New Zealand based on hearing assistance technology use? Demographic, audiometric, and health-related quality of life variables were used to measure potential factors.
Methods Participants Before commencing participant recruitment, required sample size was determined using a priori sample size analysis. The level of statistical significance was set at .05 and statistical power at .80. An effect size of d ⫽ .50, that is at least a moderate effect (Cohen, 1977), was used to define clinical meaningfulness. It was determined that 42 participants in each comparison group were required for this study. This study received approval from the University of Canterbury Human Ethics Committee prior to the commencement of participant recruitment. Participants were recruited throughout New Zealand. Recruiting methods included: newsprint media, radio media, other print media (e.g. flyers, posters), electronic media (e.g. newsletters, email lists) and word of mouth. Eligibility of those expressing interest was assessed using the following inclusion criteria: 1. 2. 3. 4.
Over the age of 18 Have verified or verifiable hearing impairment Ability to use spoken English for communication Ability to complete the information sheet and self-assessment questionnaires 5. Ability to return questionnaires to the researchers.
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Procedures Upon enrolling in the study, participants were provided with a packet that contained: (1) Demographic questionnaire, (2) Hearing handicap inventory for adults or hearing handicap inventory for the elderly as age-appropriate, (3) Medical outcomes study 36-item shortform health survey, (4) Postage paid return envelope. Participants who had a hearing test within the previous 18 months were asked to include a copy of their hearing test when returning the packet. Participants who did not have a recent hearing test were provided with one at no cost to them. Participants were invited to obtain their hearing test at the University of Canterbury Hearing Clinic if they lived conveniently close. Otherwise, participants were directed to their nearest participating audiology clinic and the University was invoiced for their hearing test. Participants who were required to obtain a hearing test were reimbursed with a $20 voucher to cover the cost of travel.
Measures Demographic information was obtained via a questionnaire. Participants were asked in an open-ended question if they owned hearing aids, and if so, how often they used them. Regular hearing-aid use was defined as a response that indicated hearing aids were worn most of the time, during waking hours, on a regular basis, etc. Similarly, participants were asked if they used any assistance technology, and if so, what they used. Participants were asked to list all the assistance devices they used. Audiometric information included pure-tone air and bone conduction thresholds, speech understanding in both quiet and noise. Pure-tone air conduction thresholds were quantified via two measures. The better hearing ear pure-tone average (BEPTA) represented the average air-conduction thresholds at 0.5, 1, 2, and 4 kHz for the better hearing ear. The worse hearing ear pure-tone average (WEPTA) represented the average air-conduction thresholds at 0.5, 1, 2, and 4 kHz for the worse hearing ear. The speech in noise test used for this study was the quick speech in noise test (QuickSIN) (Etymotic Research, 2001; Killion et al, 2004). Generic health-related quality of life was measured with the Medical Outcomes Study 36-item short-form health survey (SF-36) (Ware & Sherbourne, 1992). The SF-36 does not measure the effects of hearing impairment on an individual’s life, but rather, aims to measure overall perception of health-related quality of life. The SF-36 consists of two component scales: a physical component scale (PCS), which provides four subscale scores on components of physical health, bodily pain, role limitations due to physical health problems, and general health perceptions; and a mental component scale (MCS), which provides four further subscale scores on components of mental health, vitality, role limitations due to mental health problems, and social functioning (Abrams & Chisolm, 2007). Responses on each of the subscales can range in score from 0–100, corresponding with lowest physical or mental function to highest. The means scores for all subscales are standardized to 50, with a standard deviation of 10 (Abrams et al, 2005). Studies have shown that perception of health-related quality of life is negatively impacted by hearing impairment (Dalton et al, 2003; Hickson et al, 2008; Mulrow et al, 1990). Previous research in the non-hearing impaired population has shown that some demographic variables may impact perception of generic and disease-specific health-related quality of life. Data from international studies and from New Zealand Ministry of Health - Manatu¯ Hauora and Statistics New Zealand - Tatauranga Aotearoa have shown that scores on
both the PCS and MCS of the SF-36 are affected by age (Butterworth & Crosier, 2004; Hopman et al, 2000; Ministry of Health - Manatu¯ Hauora, 1999), income (Ministry of Health - Manatu¯ Hauora, 1999), sex (Statistics New Zealand - Tatauranga Aotearoa, 2013), and level of education (Ministry of Health - Manatu¯ Hauora, 1999). Disease-specific health-related quality of life was measured with the hearing handicap inventory for adults (HHIA) (Newman et al, 1991) for participants under the age of 65 years, and with the hearing handicap inventory for the elderly (HHIE) (Ventry & Weinstein, 1982) for participants 65 years of age and older. These two questionnaires will be collectively referred to as the “HHI”. The HHI measures the perceived psychosocial effects of hearing impairment on specific areas of a person’s life. The HHIE was developed to be used with non-institutionalized subjects aged 65 and over. The HHIA, which incorporates occupational and leisure questions, was developed for use with working adults under age 65. The HHIE and HHIA have high levels of internal consistency and test-retest reliability (0.95) and validity (0.89) (Newman et al, 1991; Weinstein et al, 1986). Both the HHIE and HHIA consist of 25 questions, which are comprised of two subscales. The emotional subscale consists of 13 questions which address the impact of hearing loss on the emotional domain of a person’s life. The second subscale, which addresses the perceived impact of hearing loss on function in social situations, consists of 12 questions. A “yes” response to any of the 25 items adds four points towards the total score, a “sometimes” adds two points, and a “no” adds zero points, for a maximum total of 100 points (Ventry & Weinstein, 1982). Participants who wore hearing aids and/or used hearing assistance technology devices were asked to complete the HHI in the unaided condition (i.e. as they are when they are not using their devices).
Results Participant summary Complete datasets were obtained from 123 participants. Many clinics in New Zealand do not routinely measure the ability to understand speech in noise and some participants had hearing impairment too great to measure supra-threshold speech understanding. Therefore, QuickSIN results were obtained for 64 participants. While the demographic questionnaire was completed by all study participants, only 92 participants reported any income. There were 53 males in this study and 70 females. The majority of participants (N ⫽ 84) listed “New Zealander” as their ancestry, 34 participants listed their ancestry as either European or North American, and five participants listed their ancestry as Ma¯ ori. Of the 123 participants who completed the study, 73 reported using at least one hearing aid on a regular basis and 50 reported not using a hearing aid on a regular basis. Of the 50 non-hearing aid users, eight reported owning at least one hearing aid but not using it on a regular basis. All of the participants who owned hearing aids (current and former users, N ⫽ 81) also reported using at least one type of hearing assistance technology device. The types of hearing assistance technology participants reported using are shown in Table 1. The 42 participants who reported never owning hearing aids also reported not using hearing assistance technology. Descriptive statistics for the study participants are shown in Table 2 and Table 3. The demographic characteristics of the population sampled in this study were not representative of the general population of NZ in terms of the following variables: the income and education level of this sample were higher than the national averages, and
HA & HAT in NZ Table 1. Hearing assistance technology used by the study participants (N ⫽ 81).
Telephone
TV/Radio
Public Alerting
Type of assistance
Number of participants
Special/amplified telephone Speaker telephone CapTel Relay/TTY Telecoil Headphones Closed captions Bluetooth Loop system FM system Device Sound dog
63 12 12 4 4 19 12 4 9 6 4 1
Note: Some participants reported using more than one type of hearing assistance technology.
the ancestry of this population reflected an under-representation of people with Ma¯ ori ancestry (Statistics New Zealand - Tatauranga Aotearoa, 2013). There was a higher proportion of females compared with males in this study in relation to the overall population in New Zealand and the hearing-impaired population. In addition, while participants lived on both the North Island and the South Island, the proportion of participants in this study living on the South Island was not reflective of the demographic trends in New Zealand (with the majority of residents living on the North Island).
Hearing-aid ownership and use One-way analysis of variance (ANOVA) and chi-square tests were performed to determine if any demographic, audiometric, and quality of life variables were significantly different between the groups based on hearing-aid use. Results of the ANOVA and Cohen’s d effect sizes for each comparison are shown in Table 2. There were no significant differences between the groups based on any demographic variable or the generic health-related quality of life questionnaire (SF-36). There were significant differences between the groups based on audiometric data and the disease-specific health-related quality of life questionnaire (HHI). Specifically, hearing-aid users had more difficulty understanding speech in background noise, had poorer hearing in their both their better and worse hearing ears, and perceived more consequences of hearing impairment in their everyday lives (both emotionally and socially) than non-hearing aid users. That is, current hearingaid users had poorer objective audiometric measures and subjective perceptions than participants who do not use hearing aids. All of the statistically significant findings had Cohen’s d effect sizes greater than .50 (moderate size) and were considered statistically significant and likely to be clinically meaningful. A discriminant analysis was performed to determine the significant variables that best classified the participants in terms of hearing-aid use. Box’s test of equality of covariance matrices was non-significant, so the assumption was not violated. A step-wise method was used and two variables were entered into the equation: HHI social and BEPTA. The discriminant equation is as follows: Di ⫽ ⫺ 7.97 ⫹ .303 (Social) ⫹ .107 (BEPTA). Using this equation, 80.5% of the original cases
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Table 2. Descriptive statistics, results of ANOVA F-test, and Cohen’s d effect sizes for hearing-aid users and non-users.
Age (years) Current HA user Non-HA user Hours worked (/week) Current HA user Non-HA user Income ($1000) Current HA user Non-HA user SNR loss (dB) Current HA user Non-HA user BEPTA (dB HL) Current HA user Non-HA user WEPTA (dB HL) Current HA user Non-HA user HHI emotional Current HA user Non-HA user HHI social Current HA user Non-HA user MCS Current HA user Non-HA user PCS Current HA user Non-HA user
Mean
Standard deviation
64.9 61.9
12.4 13.3
13.0 12.8
17.2 16.1
37.4 38.8
25.0 20.6
10.1 4.6
7.3 3.7
14.6
⬍ .001
51.6 26.1
24.3 18.8
39.2
⬍ .001
63.8 44.7
22.9 26.2
18.4
⬍ .001
.77
30.8 22.7
10.9 13.3
13.8
⬍ .001
.67
31.2 20.6
9.3 10.4
34.8
⬍ .001
72.2 70.2
19.1 19.8
.33
.56
.10
72.2 73.1
19.1 20.6
.06
.80
.04
F
p
1.7
d
.19
.23
.005
.945
.01
.07
.78
.04
.68
1.1
1.1
Current HA user ⫽ participants reporting regular use of hearing aids (N ⫽ 73). Non-HA user ⫽ participants reporting not using hearing aids on a regular basis (N ⫽ 50). SNR loss ⫽ signal-to-noise ratio loss as measured by the QuickSIN test. BEPTA ⫽ average air conduction thresholds at 0.5, 1, 2, and 4 kHz for the better hearing ear. WEPTA ⫽ average air conduction thresholds at 0.5, 1, 2, and 4 kHz for the worse hearing ear. HHI ⫽ Hearing handicap inventory. MCS ⫽ Mental component scale of the SF-36 questionnaire. PCS ⫽ Physical component scale of the SF-36 questionnaire.
were correctly classified and 78.9% of the cross validated cases were correctly classified. Cross validation is a process of assessing the accuracy of a model. If the proportion of the cross validated cases correctly classified exceeds the proportional by chance accuracy, the discriminant ability of the model is supported. In this case, the proportional by chance accuracy was calculated to be 50.2%. Thus, the discriminant ability of this model is supported.
Hearing assistance technology use Participants who reported using hearing assistance technology reported a wide variety of assistance options and many reported using more than one option. The most commonly used technology involved assistance using the telephone, with 79 hearing assistance technology users reporting using one or more devices. The next most common listening issue involved the television and/or radio. A total of 31 participants reported using a device to assist in listening in these situations. Fifteen participants reported using assistance tech-
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R. J. Kelly-Campbell & K. Lessoway
Table 3. Descriptive statistics, results of ANOVA F-test, and Cohen’s d effect sizes for hearing assistance technology users and non-users.
Age (years) HAT user HAT non-user Hours worked (/week) HAT user HAT non-user Income ($1000) HAT user HAT non-user SNR loss (dB) HAT user HAT non-user BEPTA (dB HL) HAT user HAT non-user WEPTA (dB HL) HAT user HAT non-user HHI Emotional HAT user HAT non-user HHI Social HAT user HAT non-user MCS HAT user HAT non-user PCS HAT user HAT non-user
Mean
Standard deviation
64.7 61.7
12.5 13.3
12.4 14.0
16.6 16.9
37.1 39.8
25.0 19.8
9.6 4.0
6.8 3.5
16.7
⬍ .001
50.2 23.8
23.9 18.3
39.1
⬍ .001
64.4 40.0
22.5 24.9
30.0
⬍ .001
.98
31.1 20.9
11.2 12.5
21.2
⬍ .001
.83
30.9 19.1
9.4 9.8
43.2
⬍ .001
71.8 70.6
19.6 18.8
.09
.76
.05
72.7 72.3
19.5 20.4
.01
.91
.01
F
p
d
1.5
.22
.22
.25
.61
.09
.29
.58
.09
.73
impairment in their everyday lives (both emotionally and socially) than non-hearing assistance technology users. All of the statistically significant findings had Cohen’s d effect sizes greater than .50, that is a moderate effect size, and were considered statistically significant and likely to be clinically meaningful. A discriminant analysis was performed to determine the significant variables that best classified the participants in terms of hearing assistance technology use. Box’s test of equality of covariance matrices was non-significant, so the assumption was not violated. A step-wise method was used and two variables were entered into the equation: HHI social and WEPTA. The discriminant equation is as follows: Di ⫽ ⫺ 3.67 ⫹ .092 (Social) ⫹ .03 (WEPTA). Using this equation, 81.3% of the original cases were correctly classified and 78.9% of the cross validated cases were correctly classified. The proportional by chance accuracy was calculated to be 37.9%. Thus, the discriminant ability of this model is supported.
Discussion 1.1
1.2
HAT user ⫽ participants reporting using at least one type of hearing assistance technology device (N ⫽ 81). HAT non-user ⫽ participants reporting not using any hearing assistance technology (N ⫽ 42). SNR loss ⫽ signal-to-noise ratio loss as measured by the QuickSIN test. BEPTA ⫽ average air conduction thresholds at 0.5, 1, 2, and 4 kHz for the better hearing ear. WEPTA ⫽ average air conduction thresholds at 0.5, 1, 2, and 4 kHz for the worse hearing ear. HHI ⫽ Hearing handicap inventory. MCS ⫽ Mental component scale of the SF36 questionnaire. PCS ⫽ Physical component scale of the SF-36 questionnaire.
nology in public places. Finally, four participants reported using an alerting device and one reported using a sound dog (understood by clinicians and researchers in the field). One-way analysis of variance (ANOVA) and chi-square tests were performed to determine if any demographic, audiometric, and quality of life variables were significantly different between the groups based on hearing assistance technology use. Results of the ANOVA and Cohen’s d effect sizes for each comparison are shown in Table 3. Similar to the previous analysis, there were no significant differences between the groups, based on any demographic variable, nor on the generic health-related quality of life questionnaire (SF-36). There were significant differences between the groups based on audiometric data and the disease-specific health-related quality of life questionnaire (HHI). As in the previous analysis, hearing assistance technology users had more difficulty understanding speech in background noise, had poorer hearing in their both their better and worse hearing ears, and perceived more consequences of hearing
Results of this study showed that participants did not differ in terms of demographic variables or generic health-related quality of life when classified by either hearing-aid use or hearing assistance technology use. The relationship between demographic variables and hearing-aid use is complex, and this complexity is reflected in the mixed data reported in various studies. Demographic factors such as older age, female sex, higher satisfaction with income, a family history of hearing impairment, and higher education level have been shown to have a positive relationship with ownership of hearing aids (Garstecki & Erler, 1998; Gussekloo et al, 2003; Kochkin, 1993, 2007, 2009), though not all data are supportive of these relationships (Gussekloo et al, 2003; Helvik et al, 2008). Participants in this study reported a higher income and level of education than the general New Zealand population; therefore the lack of trend present in this study may not be repeatable were a sample more reflective of the New Zealand population surveyed. Information regarding satisfaction with income, and family history of hearing impairment were not collected in this study. Participants in this study who used hearing devices reported more consequences of hearing impairment than non-device users. It is important to recall that participants were asked to complete the HHI as they function without any hearing device. Therefore the differences between the groups reflect participants’ perceptions about the underlying impact of their hearing impairment rather than the impact of hearing devices. The results of the discriminant analyses were similar for the classification of participants based on hearingaid use and on hearing assistance technology use. In both cases, the variable that best classified the participants was the social scale of the HHI. That is, it was the perceived social consequences of hearing impairment that best differentiated device users from non-users. Swan and Gatehouse (1990) argue that it is the consequences of hearing impairment on a person’s everyday life that prompts help-seeking behaviour. This notion has been supported by other researchers. Humes and colleagues (2003) controlled for gender and degree of hearing impairment and found only non-audiologic factors differentiated their groups of hearing-aid users. Gussekloo et al (2003) found mean hearing disability score was higher for those who accepted intervention than for those who rejected it. The second best classifying variable in both analyses related to hearing sensitivity. For the hearing-aid use classification, it was the better hearing ear while for the hearing assistance technology use classification, it was the worse hearing ear. Thus, device users
HA & HAT in NZ exhibited poorer hearing than non-device users. Researchers have consistently found that a perception of worsening hearing is one of the factors related to help-seeking behaviour and hearing-aid ownership (Helvik et al, 2008; Kochkin, 2009). These findings may be related to the sex (Garstecki & Erler, 1998) and age (Gusselkoo et al, 2003) of the participants. Arguably, hearing-aid ownership is not solely related to degree of hearing impairment. Other influential variables to consider are social support, perception of hearing handicap, dexterity, activity limitation, and participation restriction (Cox et al, 2005; Fischer et al, 2011; Garstecki & Erler, 1998; Gopinath et al, 2011; Helvik et al, 2008; Humes et al, 2003). Participants in this study who used hearing devices also exhibited more difficulty understanding speech in background noise than non-device users. This finding also supports previous literature (Walden & Walden, 2004). Robertson and colleagues (2012) examined variables that differentiated adults based on hearing-aid purchase decision. The groups were not significantly different in terms of demographic variables, degree of hearing impairment or ability to understand speech in quiet settings. However, they were significantly different in terms of their ability to understand speech in noise. Specifically, participants who chose to purchase hearing aids and keep them had significantly poorer SNR loss than participants who chose to return purchased hearing aids and those who chose not to purchase them. There is very little literature available with which to compare the results of the hearing assistance technology analysis, which highlights the need for additional research in this area. The similar results of the two discriminant analyses may reflect similarities in decision making for both hearing-aid and hearing assistance technology users. While data exploring predictive variables for hearing assistance technology ownership and use are lacking, the findings in this study show, overall, that distinguishing variables for both hearing assistance technology and hearing-aid users are similar for this sample. It is interesting to note that the most common hearing assistance technology reported by Greville (2005) was amplified telephones and that remains the most common assistance technology used in this sample. Participants were recruited into this study in an attempt to obtain a diverse group of adults with hearing impairment living in New Zealand that would be representative of the population. Demographically, the participants in the study did not resemble the New Zealand population in terms of income, education, sex ratio, and ancestry. In addition, a high proportion of participants lived on the South Island, which is in contrast to the demographics of New Zealand. According to the 2012 Census (Statistics New Zealand - Tatauranga Aotearoa, 2013), approximately 3.4 million people lived on the North Island, and approximately 1 million people lived on the South Island. This sampling did not achieve a true representative sample and the results of this study therefore lack some generalizability to all adults with hearing impairment living in New Zealand. Further research needs to be conducted in which participants more closely resemble the demographics of the New Zealand population. Other limitations of this study need to be considered. The study design was descriptive in nature and causal relationships between variables cannot be assumed. Another limitation of this study is the inability of the results to indicate precisely how the participants feel about the impact of hearing impairment on their lives. Just as severity of hearing impairment does not necessarily determine the extent to which one’s communication and lifestyle are impacted by hearing impairment, it is beyond the scope of health-related quality of life instruments to expand upon the meaning of the results for the
313
individual participants. That is, two individuals could have the same score on one of the health-related quality of life questionnaires used in this study, yet feel quite differently about the impact of hearing impairment upon their lives. Further research into the impact of hearing impairment on perception of health-related quality of life might include open-ended questions conducted in interview or written format. Finally, only eight study participants were former hearing-aid users and therefore analyses could not be performed on this group. More research is needed to better understand factors that are related to hearing-aid use and disuse amongst hearing-aid owners. The results of this study have potential implications for clinicians working in Aotearoa/ New Zealand. Specifically, there are four clinical suggestions that follow from these findings. First, given that the demographic variables did not discriminate device users and nonusers, clinicians are encouraged not to rely on variables such as age, gender, and income when making hearing-aid and assistive technology recommendations. Second, including disease-specific health-related quality of life measures such as the HHI in a clinical evaluation can give clinicians additional meaningful information about the impact of hearing impairment for the people they serve. Clinicians may use the information from questionnaires such as the HHI to help make device recommendations that are specifically targeted at the quality of life issues identified. Third, the results of this study also suggest clinicians would gain valuable information by employing such tools as a speech understanding in noise test alongside their pure-tone and speech audiometry because SNR loss was a variable that was found to be statistically significantly different between device users and non-users. This finding supports previous literature in regards to the positive relationship between SNR loss and hearing aid ownership (Robertson et al, 2012; Walden & Walden, 2004). Use of such tools can help validate the experience of the individual with hearing impairment and can help identify specific technology to address the problems encountered understanding speech in noise (e.g. use of directional microphones, FM, or loop systems). Finally, the results of this study suggest that adults with hearing impairment in New Zealand who use hearing aids also use hearing assistance technology. The overlap of use between these two types of devices has important clinical implications in New Zealand. Provision of hearing aids falls within the purview of audiologists and audiometrists. Provision of hearing assistance technology tends to fall within the purview of hearing therapists. It is important that these professionals work closely with each other to ensure continuity of service for hearing impaired people in New Zealand.
Conclusion In conclusion, device users (hearing aid and hearing assistance technology) were not significantly different in terms of demographic variables than non-device users. The groups were also not significantly different in terms of generic health-related quality of life, as measured by the SF-36 questionnaire. However, participants who reported using hearing aids exhibited significantly more difficulty understanding speech in background noise and significantly poorer hearing than participants who reported not using hearing aids. In addition, participants who reported using hearing aids reported poorer disease-specific quality of life (in the unaided condition) as measured by the HHI than those who reported not using hearing aids. Similar results were found for participants who reported using hearing assistance technology. These participants reported more difficulty understanding speech in background noise, significantly
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poorer hearing, and reduced disease-specific quality of life compared with participants who did not report using hearing assistance technology.
Acknowledgements We would like to acknowledge Dr Donal Sinex for his assistance with this project and in preparing this manuscript. Declaration of interest: The authors report no conflicts of interest.
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