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Article

Factors Influencing Intentions of People with Hearing Impairments to Use Augmented Reality Glasses as Hearing Aids

by
Liyuan Deng
1,
Jiangjie Chen
2 and
Dongning Li
1,*
1
School of Design, Jiangnan University, Wuxi 214122, China
2
College of Fine Arts, Huaqiao University, Quanzhou 362021, China
*
Author to whom correspondence should be addressed.
Behav. Sci. 2024, 14(8), 728; https://doi.org/10.3390/bs14080728
Submission received: 23 June 2024 / Revised: 5 August 2024 / Accepted: 20 August 2024 / Published: 21 August 2024
(This article belongs to the Special Issue Promoting Behavioral Change to Improve Health Outcomes)
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Abstract

:
The advent and progression of AR (augmented reality) technology, coupled with the emergence of AR hearing aid glasses, offer a novel opportunity for people with hearing impairments (PHI). This study aims to explore the intention of this population to employ AR hearing aid glasses as their choice of hearing aid device and the specific factors influencing their preference. This study utilized the partial least squares SEM (PLS-SEM) analytical method to create structural equation model for intentions of PHI to use AR glasses as hearing aids. Data were gathered from on-site experiences across multiple locations; a total of 189 valid questionnaires from individuals with varying degrees of hearing disabilities were used for statistical analysis. According to the data analysis results, we discovered that functionality quality, perceived interaction speed, and perceived usability significantly influence communication effectiveness. Further, communication effectiveness positively influences confidence and societal perception, and the latter has a positive impact on information. Both of these factors positively influence behavioral intention. Based on these findings, this study offers design recommendations for AR hearing aid glasses to cater to the specific needs of PHI, aiming to enhance their quality of life. Furthermore, this study provides pivotal insights for the prospective growth of this emerging industry.

1. Introduction

Hearing is one of the most important yet fragile functions in a person’s life, susceptible to various factors that can lead to hearing loss at any time for anyone [1,2,3]. As a result, hearing impairment has become the third most common cause of disability [4,5]. According to the World Hearing Report published by the World Health Organization, by 2021, over 5% of the global population suffered from hearing loss, and by 2050, it is projected that nearly 2.5 billion individuals will have different degree of hearing loss [6]. Hence, hearing impairment has gravely threatened global public health [7,8,9].
Unlike individuals who are deaf, people with hearing impairments (PHI), despite facing various difficulties due to hearing loss [10,11], can address these issues with the help of hearing aid products [12]. However, the adoption rate of assistive devices in the real-world context remains low among PHI [13,14]. Among them, hearing aids are the primary choice for hearing impairment rehabilitation [15,16,17], yet their adoption rate is less than 20% [18]. One of the main reasons for this phenomenon is the stigma associated with them [19,20]. Because hearing impairment is an invisible disability, the use of such assistive devices may inadvertently highlight it, leading to the bearer being labeled or perceived as disabled or an outsider in society [21,22,23,24,25,26]
Consequently, many individuals, before seeking medical intervention and receiving a diagnosis of hearing impairment, may prefer to experiment with devices that appear “normal” in any public setting, such as smart glasses [27,28,29], mobile phones [30,31], and smart earbuds like AirPods and Samsung Galaxy Buds Pro [32]. However, mobile phones as hearing-assistive agents are not suitable for everyday face-to-face communication, and smart earbuds, which merely amplify sounds, might risk further deterioration in hearing. In contrast, smart glasses offer advantages such as a natural appearance, sensory compensation, comfortable wear, and a broad range of applicability. They emerge as a superior choice. As dos Santos, Ferrari [33] pointed out, both glasses and hearing aids can assist those with hearing difficulties, but the stigma associated with glasses is significantly less.
With the advancement and proliferation of augmented reality (AR) technology, AR glasses demonstrate greater potential as hearing aid devices [28,33]. With AR technology, hearing-assistive glasses have transcended their basic function of merely integrating sound amplifiers into their frames. Instead, they now incorporate AR tech into the lens interface and visual effects, amalgamating features like real-time voice-to-text captions, specialized word prompts, spatial sound indicators, etc., into the AR glasses display system, enabling users with hearing impairments to communicate normally through AR glasses [29,34]. It is evident that AR hearing glasses have unique advantages in terms of technological functionality, social acceptance, and interactive experience. As a hearing aid device, they possess immense growth potential and a vast market outlook, holding significant social and economic value.
Given the anticipated significant increase in the number of PHI over the next 30 years, understanding their attitudes towards adopting and intention to use hearing-assistive technology is crucial [6,35]. However, current research on the adoption and usage of hearing aid devices mainly focuses on traditional hearing aids [36,37,38], and studies on the emerging product of AR hearing glasses are relatively scarce. Existing research on AR hearing aid glasses primarily centers on technological development, functional innovation, experience design, and product development [14,27,28,29,34,39], with insufficient exploration of whether PHI can truly accept and use AR hearing aid glasses. Most studies approach the issue from a single perspective, either technological functionality or sociocultural aspects [40,41,42,43,44], with few studies comprehensively exploring the willingness of PHI to adopt AR hearing aid glasses from an integrated perspective.
Therefore, this study, based on sociotechnical systems theory (STS), explores the factors and mechanisms influencing the intention of PHI to use AR hearing aid glasses from a comprehensive perspective encompassing technical, social, and individual dimensions. This research aims to provide insights and references for optimizing the design and enhancing the acceptance of AR hearing aid glasses, offering a new practical direction to improve the communication experience and social integration of PHI.

2. Theoretical Framework and Research Hypotheses

Sociotechnical systems theory (STS) is an interdisciplinary theory that provides a comprehensive perspective for understanding and designing technological systems by considering the complex interactions between technical, social, and individual factors [45,46]. The core idea of this theory is that various subsystems (technical, social, and individual) are interdependent and mutually influential. The design and implementation of any new technology, product, or service system must simultaneously consider the potential impacts on these subsystems to achieve optimal results [47,48]. This paper adopts the three-dimensional framework of sociotechnical systems theory—technical subsystem, social subsystem, and individual subsystem—as the theoretical foundation for the following reasons: On one hand, sociotechnical systems theory provides a comprehensive analytical framework for emerging issues related to hearing impairment behavior, hearing aid technology, and AR hearing glasses. On the other hand, research on hearing impairment and hearing aid technology is not merely a technical or individual health issue; it is a complex phenomenon that encompasses personal physiology, product technical functions, and social life [33,49]. Through the integrated perspective of sociotechnical systems theory, we can gain a more comprehensive understanding of the motivations and behavioral impact mechanisms of PHI using AR hearing glasses.
Based on the three dimensions of sociotechnical systems theory, this study explores the technical features of AR hearing aid glasses, the personal physiological characteristics of PHI, and the relevant factors of social life. It ultimately identifies seven factors, namely: functional quality, perceived interaction speed, perceived ease of use, communication effectiveness, social image, confidence, and behavioral intention. The operational definitions for each construct are presented in Table 1.

2.1. Function Quality

PHI use the functions of hearing aids to compensate for their hearing deficits [57]. The quality of these functions signifies the quality of sound information reception for them. Clear and consistent information is a significant influencing factor in interpersonal communication [58]. Therefore, the features of the hearing aids affect communication outcomes [59]. Many studies have also confirmed that the better the performance of hearing aids (such as noise suppression, clarity compensation, etc.), the better the communication outcomes for PHI in various scenarios [28,60,61,62,63]. Hence, this study proposes the following hypothesis:
Hypothesis 1 (H1). 
The functional quality of AR smart glasses has a positive impact on the communication outcomes of PHI.

2.2. Perceived Interaction Speed

Research indicates that in interpersonal communication, the speed of interaction between people (speaking rate, cohesion speed, pause intervals, etc.) is one of the three main dimensions for achieving smooth communication. There is a significant relationship between the speed of interaction and the quality of communication [64,65,66]. For PHI, due to their hearing loss, they cannot communicate directly with those without hearing impairments but must do so mediated by hearing aids. Therefore, hearing aid products are considered an additional pair of ears for PHI [67]; the interaction speed of the hearing aids signifies the sensitivity and reaction speed of their “ears”. Gugenheimer, Plaumann [59] found that interruptions in conversation reduce communication quality. Conversely, if the device’s real-time interaction speed is fast enough, synchronous dialogue can be achieved [68], reducing interruptions during communication and thereby enhancing communication quality. Therefore, the faster the interaction speed of the AR smart glasses, the better the communication outcome. Based on this, this study proposes the following hypothesis:
Hypothesis 2 (H2). 
The perceived interaction speed of AR smart glasses by PHI has a positive impact on communication outcomes.

2.3. Perceived Ease of Use

In this study, perceived ease of use refers to the degree of ease or difficulty that users with hearing impairments feel when using AR glasses. The literature has already confirmed that there is a significant relationship between perceived ease of use and communication [69,70]. Additionally, some studies have proven that the perceived ease of use of technology products designed for social communication has a positive impact on communication outcomes [71,72]. For example, Chan, Yong, and Harmizi [72] examined the relationship between the use of WhatsApp by students at private higher education institutions in Malaysia and interpersonal communication, confirming a positive correlation between perceived ease of use and interpersonal communication. Based on this, this study proposes the following hypothesis:
Hypothesis 3 (H3). 
The perceived ease of use of AR smart glasses has a positive impact on the communication of PHI.

2.4. Communication Effectiveness

Being able to communicate with people who have unimpaired hearing is crucial for those with hearing impairments [59]. Many studies have confirmed that good communication interactions positively influence confidence enhancement [73,74]. Blood, Blood [75] pointed out in their study that stuttering adolescents may lack confidence in their communication abilities due to communication difficulties. Conversely, smooth communication can boost self-confidence. In the field of assistive hearing device research, enhancing the communication capabilities of users with hearing impairments through relevant products, technologies, and services can alleviate the anxiety and stress caused by fear [76,77], which in turn can further boost the confidence of users with hearing impairments [78,79,80].
There is a close relationship between communication and social image [81,82,83,84]. Lin and Bhattacherjee [54] confirmed in their study that users’ social communication with others in social networks positively impacts the creation of a favorable social image. Heffernan, Coulson [85] pointed out that the stigmatization and damage to the social image of PHI often result from communication difficulties. By achieving normal and free communication through technology without revealing their unique health status, PHI can avoid being seen as disabled, thus sidestepping stigmatized views and attitudes, and achieving equality and respect [86], which translates to a positive social image. Therefore, when AR hearing-assistive glasses help users with hearing impairments to communicate smoothly and avoid stigmatization, they can help these users establish a good social image. Hence, this study proposes the following hypotheses:
Hypothesis 4 (H4). 
Communication effectiveness has a positive impact on the shaping of the social image of PHI.
Hypothesis 5 (H5). 
Communication effectiveness has a positive impact on the confidence of PHI.

2.5. Social Image

Social image is defined as the extent to which users can obtain opinions and respect from their peers, family members, or others in their social relationships [87]. There is also a close relationship between social image and confidence. Confidence, in the context of personal motivation, explains why and to what extent people care about their self and social image, indicating that social image has a positive effect on confidence [88]. Lubis and Fazira [89] pointed out in their study that there is a significant positive correlation between social support (which includes the concept of social image) and confidence. In disability research, the role of social image in confidence is even more evident [90]. Simsek, Evli [91], in the context of chronic illness research, found a positive correlation between body image and confidence. Therefore, consistent with previous research, a good social image can enhance the confidence of the hearing-impaired group.
The study of social image in interactive products is of great significance. As the image of users comes from the opinions and views of others, users will thus decide on subsequent actions based on these views [92]. Some of the literature has confirmed that the social image produced by users using products or systems will significantly affect the subsequent intention to use [54,87,93]. Bispo and Branco [94] pointed out that the design of assistive technology for people with disabilities might change their social image. The same is true for hearing-assistive products—non-stigmatizing design may stimulate users’ desire and behavior to use [33]. AR smart glasses are generally not associated with one’s mental image of disability; this can reduce stigmatization, thus forming a good social image. To maintain this good social image, PHI may continue to choose to use AR glasses in the future. Based on the above discussion, this study proposes the following hypotheses:
Hypothesis 6 (H6). 
The social image formed by PHI during the use of AR glasses has a positive impact on their confidence.
Hypothesis 7 (H7). 
The social image formed by PHI during the use of AR glasses has a positive impact on their behavioral intention.

2.6. Confidence

Confidence can be defined as an individual’s belief in their abilities, a state of certainty about the success of a specific behavior [95]. The relationship between confidence and behavioral intention has been confirmed in many studies [96,97,98]. For instance, Kim, Ahn, and No [97] pointed out in their study that confidence in one’s physical health affects the choice and execution of behavior. Chai, Lin [98] found in their research that confidence in AI technology is positively correlated with the intention to continue using AI devices. In line with previous studies, this research believes that the confidence of PHI in the AR glasses technology assisting them in smooth communication has a positive impact on the intention to continue using AR glasses. Therefore, this article proposes the following hypothesis:
Hypothesis 8 (H8). 
The confidence gained from social communication through AR glasses has a positive impact on PHI’s intention to continue using AR glasses.
Based on the discussions in the previous sections, this study formulates eight hypotheses. The path and hypothesis model are shown in Figure 1.

3. Questionnaire Design and Data Collection

3.1. Questionnaire Design

This study combined the product features of AR hearing aid glasses with the characteristics of the research to design a literature-validated questionnaire (see Table 2). After completing the initial questionnaire design, we conducted a pretest with 30 participants and adjusted the questionnaire based on their feedback. The final version included basic information and an assessment of factors influencing the use of AR hearing aid glasses. (using a Likert’s seven-point scale).

3.2. Data Collection

The research and experimentation for this study spanned eight months. During the preliminary preparation phase from January to April 2023, we conducted an initial screening of hearing-impaired subjects, visited multiple locations, tested and selected experimental tools, and designed and evaluated the questionnaire. From May to August 2023, we carried out formal questionnaire surveys at hearing centers and service institutions in Wuxi, Xiamen, Hangzhou, and other cities in China, using both offline experiences and online questionnaires. We employed a cluster sampling technique. Conducting surveys through established hearing centers and service institutions provided practical benefits, as it allowed for us to efficiently recruit a large number of participants within the given timeframe. Additionally, this approach enabled us to capture a broad range of experiences and perspectives from participants across various locations.
We used the LEION HEY AR smart glasses as the testing tool and invited participants to complete the questionnaire after experiencing the product for more than 15 min. After screening, a total of 189 valid questionnaires were collected. The demographic information of the respondents is shown in Table 3.

4. Data Analysis and Results

This study employs the partial least squares structural equation modeling (PLS-SEM) research method. As a flexible multivariate analysis approach, PLS-SEM is utilized for constructing and validating complex structural equation models [107]. Therefore, this study utilized the PLS-SEM algorithm in SmartPLS 4 V4.0.9.2, employing a weighted path scheme, with a maximum of 3000 iterations and default initial weights. Further, we used path analysis techniques to verify the eight proposed hypotheses. Finally, we integrated the empirical data and conducted an in-depth analysis within the existing theoretical framework, and then drew rigorous conclusions.
This study employed the SmartPLS software to calculate the reliability and validity of constructs, specifically considering three indicators: Cronbach’s alpha, composite reliability, and average variance extracted (AVE). As shown in Table 4, the Cronbach’s alpha value for each construct in this study exceeded 0.7, and the rho_c value also exceeded 0.7, indicating that all the constructs used have good reliability. Next, this study used AVE to measure convergent validity. The usual standard is for AVE to be greater than 0.5. All the indicators in this study meet this requirement [108]. Therefore, the constructs in this study exhibit good convergent validity.
If the square root of the AVE value of each construct is greater than the correlation coefficients between itself and other constructs, it suggests that the scale has good discriminant validity [109]. As shown in Table 5, the bold numbers on the diagonal represent the square root of the AVE values for each construct, which are all greater than the correlation coefficients, which indicates that there is good discriminant validity between the constructs used in this study.
This study also uses the HTMT (heterotrait/monotrait ratio) method to evaluate the discriminant validity of the constructs [110]. According to previous research, the HTMT value must be less than 0.9 [111]. As shown in Table 6, the HTMT values for all constructs are less than 0.9. Therefore, all constructs in this study have good discriminant validity.
Also, during this stage, additional measures were evaluated, namely, the determination coefficient (R2) and predictive relevance (Q2) [108]. As shown in Table 7, the R2 values between the constructs range from 46.9% to 66.9%. R2 values greater than 26% are considered significant [112]. In this study, the Q2 values of the constructs (calculated only for dependent variables) are all non-zero. Therefore, the hypothesized model in this study has acceptable predictive relevance [113]. Additionally, indicators such as the standardized root mean square residual (SRMR) and the normed fit index (NFI) were used to evaluate the fit of the structural equation model (see Table 8). The SRMR value is 0.082, which is below the threshold of 0.10, and the NFI value is 0.804, where an NFI value close to 1 indicates a good model fit. These fit indices suggest that the hypothesized model proposed in this study performs well in explaining the data structure.
The bootstrapping procedure (with 5000 bootstrap resampling) was applied to further test the proposed hypotheses. The results of the model path analysis are shown in Figure 2, and the regression coefficient results of the structural equation model are shown in Table 9. The results indicate that all hypotheses of this study are supported. Furthermore, the full collinearity test results show that the variance inflation factor (VIF) ranges between 1.000 and 2.674. All the VIFs are below the recommended threshold of 5 [108], confirming that there is no multicollinearity issue in the estimated model of this study.

5. Discussion

According to the research results, function quality and perceived interactivity speed have a significant positive impact on communication effectiveness (H1 and H2 are supported). The previous literature has pointed out that hearing aids can be considered an additional pair of ears for users with hearing impairments [67]. The quality and speed of their functions are equivalent to the clarity and sensitivity of these “ears”. AR hearing aid glasses serve as an intermediary for PHI to interact with external sounds. The higher the functional quality of AR hearing aid glasses, the clearer the external sounds they read, and the more accurate the converted text information, leading to better communication effectiveness for the user. Similarly, if AR hearing aid glasses can quickly capture, process, and present visual information, enabling PHI to swiftly acquire conversation content, speech-to-text information, and respond accordingly, this instant feedback helps reduce delays and misunderstandings in communication. This allows for a synchronized rhythm with others, avoiding interruptions in conversations, making the entire communication process more natural, relaxed, and smooth [59], thereby enhancing the communication effectiveness for PHI.
Perceived ease of use has a significant positive impact on communication effectiveness (H3 is supported). Unlike traditional hearing aids, which users cannot control independently, AR hearing aid glasses offer more functions, meaning there may be many aspects requiring user operation. Although most functions are set up before communication interactions, the complexity of social situations and the unpredictability of human behavior can lead to changes in social communication conditions and needs [114]. This, in turn, necessitates adjustments to the AR hearing aid glasses, such as font size, color, and contrast, as well as turning on the device or adjusting the volume. If these adjustments can be easily made during conversations, PHI can focus more on the communication itself, thereby enhancing the effectiveness and experience of their interactions.
It is worth noting that even though function quality, perceived interaction speed, and perceived ease of use all have significant positive impacts on communication effectiveness, and perceived ease of use has a stronger influence on communication effectiveness (0.426 > 0.256 > 0.250). The reason for this might be related to the unique ways PHI receive information and their cognitive processing methods. PHI are not completely deaf; they still retain some degree of hearing ability. Before using hearing aids, PHI might intentionally or unintentionally employ various skills to complement this portion of sound information. For example, they imagine and reason to fill in the details not fully heard in conversations, especially for unclear words and phrases. They may also use non-verbal strategies to enhance communication, such as observing the speaker’s lip movements, body language, facial expressions, and contextual environment to infer the meaning, emotions, and attitudes in the conversation [115,116,117]. By utilizing these techniques, PHI can combine their existing knowledge, memory, and experience to partially fill in the missing information and deduce the logical conclusions of the conversation [118]. Thus, for AR hearing-assistive glasses, even if the accuracy of voice-to-text isn’t very high or the conversion speed is slow, individuals can still construct a complete dialogue scene using their imagination and reasoning skills. In contrast, the perceived ease of use of AR hearing-assistive glasses has a more significant effect on communication. On the one hand, the usage method of AR hearing aid glasses differs significantly from traditional hearing aids. Traditional hearing aids require little to no manual operation during daily use, whereas AR hearing aid glasses necessitate user interaction. This interaction can occur at any stage before, during, or after communication, emphasizing the importance of ease of use. On the other hand, the user’s operation of the glasses is explicit and visible to both parties. If the glasses are challenging to use, users might need to adjust them repeatedly during conversations, not only wasting time and causing communication delays but also diverting their attention. Not focusing on the interlocutor during a conversation is considered impolite and might make the other party feel disrespected [119]. Therefore, the influence of perceived ease of use on communication effectiveness can create a chain reaction, much like the butterfly effect, resulting in a stronger impact.
Secondly, communication effectiveness has a significant positive impact on both social image and confidence (H4 and H5 are supported). With the assistance of AR glasses, effective two-way communication enables clear understanding and expression of information, preventing many awkward situations such as being unable to participate in group conversations, missing important information, or not responding promptly. This helps to avoid feelings of marginalization and inferiority, thereby enhancing conversational confidence. Furthermore, the stigmatization and negative social image of those with hearing impairments are often directly related to communication challenges [85]. With the support of AR hearing-assistive glasses, PHI can establish effective two-way communication, build a positive image, and gain more recognition, respect, and equality in social life, education, and career development [86].
Social image has a significant positive impact on confidence (H6 is supported), which is consistent with the findings of previous studies [89,90,91]. According to Tajfel and Turner [120], when individuals feel recognized and affirmed within their social group, their confidence is boosted. PHI often do not consider themselves having a disability [121]. Therefore, they desire to establish an image of capability equal to those with without impaired hearing. However, this desire often contradicts the use of hearing-assistive devices because the distinctive appearance of most of these devices inadvertently reveals their hearing deficiencies. Unlike other hearing aids that might expose one’s hearing challenges, AR glasses possess high social acceptability and low stigmatization. They can enhance communication abilities without disclosing hearing impairments. Once this positive social image is recognized by others, it can boost positive emotions and confidence.
Lastly, both social image and confidence have a significant positive impact on the intention to use (H7 and H8 are supported). In social life, individuals not only perceive themselves as independent entities but also as members of social groups, and they seek recognition from these groups [120]. Therefore, the social image is crucial. When PHI gain a wholesome social image by using AR glasses, integrating them into the mainstream group, they are more likely to accept and adopt hearing-assistive technology. Conversely, devices that expose their hearing deficiencies are likely to be rejected [122]. Furthermore, compared to social image, confidence has a stronger impact on the intention to use (0.534 > 0.296). This might be due to confidence serving as an intrinsic factor, exerting a more direct inner drive on usage intention, while the social image, as an external factor, primarily plays a supporting role. The construction of social image is rooted in others’ perceptions and attitudes, an external push. This external force typically undergoes self-awareness, filtration, absorption, and rational analysis before it internalizes and influences behavior. Throughout this process, users filter some external factors based on their self-perception, reducing the impact of these factors to some extent. In contrast, confidence, being an intrinsic driver, can directly influence behavior choices [123], and hence has a more potent influence.

6. Contributions and Limitations

This study, based on sociotechnical systems theory, explores the factors influencing the intention of PHI to use AR glasses as hearing aid devices from a comprehensive perspective of technological, social, and individual levels. It identifies the real needs and decision-making mechanisms of PHI, enriching the theoretical foundation of the hearing aid design field and providing practical guidance and insights.

6.1. Theoretical Contributions

(1).
This study enriches the field of behavioral research in hearing impairment and design. By introducing sociotechnical systems theory into the study of hearing impairment behavior, it explores how the interaction between technological, social, and individual dimensions affects the experience of PHI using AR hearing aid glasses, thereby influencing their subsequent adoption intentions. This research provides a new explanatory pathway for the behavior of PHI using AR hearing glasses and offers a theoretical framework for further understanding and recognizing the deep needs of PHI. It also provides theoretical support for the development and design of hearing impairment treatments, services, and related products. Furthermore, this study helps overcome the limitations of technocentrism and partial perspectives in hearing impairment research.
(2).
Through quantitative analysis, this study elucidates the intrinsic mechanisms and decision-making pathways for PHI choosing AR glasses as hearing aid devices. Specifically, it identifies that social image and confidence are the decisive factors influencing users’ intention to use AR hearing aid glasses, while the technical aspects of functional quality, perceived interactivity speed, and perceived ease of use are merely necessary prerequisites and foundations and do not directly determine the intention to use AR hearing aid glasses. This finding aligns with the general direction of existing research on hearing impairment and hearing aid technology, providing further empirical evidence. Additionally, by examining specific aspects and more tangible product targets, this study clarifies the intrinsic relationships and influencing mechanisms between variables at the technical, social, and individual levels and the intention to use AR hearing glasses. This provides more targeted theoretical guidance for strategy formulation and practical implementation in the field of hearing aid technology and services.

6.2. Practical Contributions

In terms of practical implications, the results of this study make tangible contributions to expanding the market for AR hearing-assistive glasses and sustainable development. By clarifying various factors influencing the use of AR glasses as hearing-assistive devices by PHI, this study provides a research foundation and guiding direction for the development of AR hearing-assistive glasses and other hearing-assistive products. It offers recommendations and design strategies for optimizing their design, mainly including the following:
(1).
In the development of AR hearing-assistive glasses, special attention should be given to the interactive ease-of-use design of the AR glasses. The basic operations of the AR glasses should be simplified to prevent users from abandoning their use due to difficulty. Consideration can even be given to employing the most advanced intelligent proactive interactive methods, allowing for the device to autonomously complete interactions based on circumstances. This avoids tedious operations during communication and allows for users to focus on communicating, thereby enhancing the communication experience.
(2).
It is essential to integrate as many functions as possible, such as noise reduction, multi-directional microphone pickups, and adaptive light brightness adjustments and ensure the high quality of these features to assist PHI in communicating normally in various environments. It is also vital to improve the interaction speed of AR hearing-assistive glasses, such as the response speed for keyword activation and the speed of voice-to-text, so that PHI can maintain a consistent rhythm with their counterparts during communication.
(3).
The design of AR glasses should closely resemble regular glasses used in daily life. The lens can adopt a single-sided design to ensure the virtual interface is not visible to others, thus avoiding excessive attention. This helps PHI rid themselves of the “special” label, thereby building social confidence. It is also essential to design the text information’s display size, color, transparency, and position well, so users can clearly view the text while not obscuring the eyes and non-verbal actions of others. This facilitates more eye contact during communication, allowing for users to express their sincerity, earn the respect of others, establish a positive social image, and better integrate into various aspects of life, education, and work.

6.3. Research Limitations

While this study offers valuable contributions both theoretically and practically, there are still some limitations. On one hand, due to objective constraints such as culture, funding, geography, and time, we encountered many obstacles when trying to locate PHI, making it difficult to expand our sample size. On the other hand, since AR hearing-assistive glasses are an emerging product, most of our respondents were completely unfamiliar with them. This may lead to self-report biases and potential errors in data validity. Although we made efforts to minimize these biases by providing product descriptions, allowing participants to try the glasses and offering guidance as necessary before they filled out the questionnaire, we still recognize that this limitation could mislead our study’s results. Therefore, when interpreting and promoting the findings of this study, potential uncertainties arising from data biases should be carefully considered. Moreover, there are numerous areas for further detailed research. For instance, PHI from different age groups may have varied attitudes towards AR glasses. Our study, with its limited sample, did not differentiate the intention to use based on age groups. Secondly, different genders might have different preferences for the design and aesthetics of hearing-assistive devices. Thirdly, acceptance of AR hearing-assistive glasses might be influenced to different degrees in various countries and cultural environments. Future research can build upon the foundation of this study and further segment personal attributes and societal scopes, allowing for more targeted and in-depth exploration of AR hearing-assistive glasses.

Author Contributions

Conceptualization, L.D.; Methodology, J.C.; Resources, D.L.; Data curation, L.D.; Writing—original draft, L.D.; Writing—review & editing, D.L.; Supervision, D.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Changshu Institute of Technology Ministry of Social Science (protocol code No. CIT MSS-E-2023-011 and date of 25 May 2023 approval).

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

We would like to thank Jiangnan University and Changshu Institute of Technology for providing the equipment and technical support for this research. Special thanks to Weiwei from Changshu Institute of Technology for offering detailed ethical guidance and supervision in the design of the questionnaire and the standardization of the experimental process.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Roizen, N.J. Nongenetic causes of hearing loss. Ment. Retard. Dev. Disabil. Res. Rev. 2003, 9, 120–127. [Google Scholar] [CrossRef] [PubMed]
  2. Daniel, E. Noise and Hearing Loss: A Review. J. Sch. Health 2007, 77, 225–231. [Google Scholar] [CrossRef] [PubMed]
  3. Willems, P.J. Genetic Causes of Hearing Loss. N. Engl. J. Med. 2000, 342, 1101–1109. [Google Scholar] [CrossRef]
  4. Tonelli, M.; Warick, R. Focusing on the Needs of People with Hearing Loss During the COVID-19 Pandemic and Beyond. JAMA 2022, 327, 1129–1130. [Google Scholar] [CrossRef]
  5. Kim, S.Y.; Min, C.; Yoo, D.M.; Chang, J.; Lee, H.-J.; Park, B.; Choi, H.G. Hearing Impairment Increases Economic Inequality. Clin. Exp. Otorhinolaryngol. 2021, 14, 278–286. [Google Scholar] [CrossRef] [PubMed]
  6. World Health Organization. World Report on Hearing: Executive Summary; World Health Organization: Geneva, Switzerland, 2021. [Google Scholar]
  7. Swanepoel, W.; De Sousa, K.C.; Smits, C.; Moore, D.R. Mobile applications to detect hearing impairment: Opportunities and challenges. Bull. World Health Organ. 2019, 97, 717–718. [Google Scholar] [CrossRef] [PubMed]
  8. Miao, L.; Wang, B.; Zhang, J.; Yin, L.; Pu, Y. A functional SNP in miR-625-5p binding site of AKT2 3′UTR is associated with noise-induced hearing loss susceptibility in the Chinese population. Environ. Sci. Pollut. Res. 2021, 28, 40782–40792. [Google Scholar] [CrossRef]
  9. Olusanya, B.O.; Davis, A.C.; Hoffman, H.J. Hearing loss: Rising prevalence and impact. Bull. World Health Organ. 2019, 97, 646–646a. [Google Scholar] [CrossRef] [PubMed]
  10. Shukla, A.; Harper, M.; Pedersen, E.; Goman, A.; Suen, J.J.; Price, C.; Applebaum, J.; Hoyer, M.; Lin, F.R.; Reed, N.S. Hearing Loss, Loneliness, and Social Isolation: A Systematic Review. Otolaryngol. Head Neck Surg. 2020, 162, 622–633. [Google Scholar] [CrossRef]
  11. Ohlenforst, B.; Zekveld, A.A.; Jansma, E.P.; Wang, Y.; Naylor, G.; Lorens, A.; Lunner, T.; Kramer, S.E. Effects of hearing impairment and hearing aid amplification on listening effort: A systematic review. Ear Hear. 2017, 38, 267. [Google Scholar] [CrossRef] [PubMed]
  12. World Health Organization. Deafness and Hearing Loss. 2023. Available online: https://www.who.int/news-room/fact-sheets/detail/deafness-and-hearing-loss (accessed on 2 February 2024).
  13. Sawyer, C.S.; Armitage, C.J.; Munro, K.J.; Singh, G.; Dawes, P.D. Correlates of hearing aid use in UK adults: Self-reported hearing difficulties, social participation, living situation, health, and demographics. Ear Hear. 2019, 40, 1061–1068. [Google Scholar] [CrossRef] [PubMed]
  14. Takaki, K.; Nozaki, E.; Kanai, T.; Hautasaari, A.; Kashio, A.; Sato, D.; Kamogashira, T.; Uranaka, T.; Urata, S.; Koyama, H. asEars: Designing and Evaluating the User Experience of Wearable Assistive Devices for Single-Sided Deafness. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, New York, NY, USA, 23–28 April 2023; pp. 1–17. [Google Scholar]
  15. Kawata, N.; Nouchi, R.; Oba, K.; Matsuzaki, Y.; Kawashima, R. Auditory cognitive training improves brain plasticity in healthy older adults: Evidence from a randomized controlled trial. Front. Aging Neurosci. 2022, 14, 140. [Google Scholar] [CrossRef]
  16. Putri, S.S.; Supena, A.; Yatimah, D. Utilization of Internet Media by Deaf Persons for Language Learning (Case study on 11-year-old child at SLB B Tunas Kasih 2, Bogor City, West Java). In Proceedings of the International Conference on Education, Science and Technology, West Sumatera, Indonesia, 13–16 March 2019; pp. 151–157. [Google Scholar]
  17. Chung, S.-H.; Jeong, S.W.; Kim, L.-S. A case of auditory neuropathy caused by pontine hemorrhage in an adult. J. Audiol. Otol. 2017, 21, 107. [Google Scholar] [CrossRef]
  18. Wu, H.C.; Thallmayer, T.; Deal, J.A.; Betz, J.F.; Reed, N.S.; Lin, F.R. Prevalence Trends in Hearing Aid Use among US Adults Aged 50 to 69 Years with Hearing Loss—2011 to 2016 vs. 1999 to 2004. JAMA Otolaryngol. Head Neck Surg. 2021, 147, 831–832. [Google Scholar] [CrossRef]
  19. Gagné, J.-P.; Southall, K.; Jennings, M.B. Stigma and self-stigma associated with acquired hearing loss in adults. Hear. Rev. 2011, 18, 16–22. [Google Scholar]
  20. KochKiN, S. MarkeTrak VIII: The key influencing factors in hearing aid purchase intent. Hear. Rev. 2012, 19, 12–25. [Google Scholar]
  21. Kochkin, S. MarkeTrak VII: Obstacles to adult non-user adoption of hearing aids. Hear. J. 2007, 60, 24–51. [Google Scholar] [CrossRef]
  22. Jenstad, L.; Moon, J. Systematic review of barriers and facilitators to hearing aid uptake in older adults. Audiol. Res. 2011, 1, e25. [Google Scholar] [CrossRef] [PubMed]
  23. Meister, H.; Walger, M.; Brehmer, D.; von Wedel, U.-C.; von Wedel, H. The relationship between pre-fitting expectations and willingness to use hearing aids. Int. J. Audiol. 2008, 47, 153–159. [Google Scholar] [CrossRef] [PubMed]
  24. David, D.; Werner, P. Stigma regarding hearing loss and hearing aids: A scoping review. Stigma Health 2016, 1, 59. [Google Scholar] [CrossRef]
  25. Southall, K.; Gagné, J.-P.; Jennings, M.B. Stigma: A negative and a positive influence on help-seeking for adults with acquired hearing loss. Int. J. Audiol. 2010, 49, 804–814. [Google Scholar] [CrossRef] [PubMed]
  26. Ruusuvuori, J.E.; Aaltonen, T.; Koskela, I.; Ranta, J.; Lonka, E.; Salmenlinna, I.; Laakso, M. Studies on stigma regarding hearing impairment and hearing aid use among adults of working age: A scoping review. Disabil. Rehabil. 2021, 43, 436–446. [Google Scholar] [CrossRef]
  27. Xu, M.; Li, J. Design of an AR Realistic Interactive Hearing Aid System Based on Digital Construction. Packag. Eng. 2023, 44, 404–410. (In Chinese) [Google Scholar] [CrossRef]
  28. Mehra, R.; Brimijoin, O.; Robinson, P.; Lunner, T. Potential of Augmented Reality Platforms to Improve Individual Hearing Aids and to Support More Ecologically Valid Research. Ear Hear. 2020, 41, 140s–146s. [Google Scholar] [CrossRef] [PubMed]
  29. Ridha, A.M.; Shehieb, W. Assistive technology for hearing-impaired and deaf students utilizing augmented reality. In Proceedings of the 2021 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), Virtual, 12–17 September 2021; pp. 1–5. [Google Scholar]
  30. Amlani, A.M.; Taylor, B.; Levy, C.; Robbins, R. Utility of smartphone-based hearing aid applications as a substitute to traditional hearing aids. Hear. Rev. 2013, 20, 16–18. [Google Scholar]
  31. Slaney, M.; Lyon, R.F.; Garcia, R.; Kemler, B.; Gnegy, C.; Wilson, K.; Kanevsky, D.; Savla, S.; Cerf, V.G. Auditory measures for the next billion users. Ear Hear. 2020, 41, 131S–139S. [Google Scholar] [CrossRef]
  32. Ochsner, B.; Spöhrer, M.; Stock, R. Rethinking assistive technologies: Users, environments, digital media, and app-practices of hearing. NanoEthics 2022, 16, 65–79. [Google Scholar] [CrossRef]
  33. dos Santos, A.D.P.; Ferrari, A.L.M.; Medola, F.O.; Sandnes, F.E. Aesthetics and the perceived stigma of assistive technology for visual impairment. Disabil. Rehabil. Assist. Technol. 2022, 17, 152–158. [Google Scholar] [CrossRef]
  34. Dufraux, A.; Vincent, E.; Hannun, A.; Brun, A.; Douze, M. Lead2Gold: Towards exploiting the full potential of noisy transcriptions for speech recognition. In Proceedings of the 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), Singapore, 14–18 December 2019; pp. 78–85. [Google Scholar]
  35. Chang, P.F.; Tucker, R.V. Assistive Communication Technologies and Stigma: How Perceived Visibility of Cochlear Implants Affects Self-Stigma and Social Interaction Anxiety. Proc. ACM Hum. Comput. Interact. 2022, 6, 77. [Google Scholar] [CrossRef]
  36. Chang, V.; Wang, Y.; Wills, G. Research investigations on the use or non-use of hearing aids in the smart cities. Technol. Forecast. Soc. Change 2020, 153, 119231. [Google Scholar] [CrossRef]
  37. Desjardins, J.L.; Sotelo, L.R. Self-Reported Reasons for the Non-Use of Hearing Aids among Hispanic Adults with Hearing Loss. Am. J. Audiol. 2021, 30, 709–716. [Google Scholar] [CrossRef] [PubMed]
  38. Sawyer, C.S.; Munro, K.J.; Dawes, P.; O’Driscoll, M.P.; Armitage, C.J. Beyond motivation: Identifying targets for intervention to increase hearing aid use in adults. Int. J. Audiol. 2019, 58, 53–58. [Google Scholar] [CrossRef] [PubMed]
  39. Brown, K.; Pullin, G. Uncovering Nuance: Exploring Hearing Aids and Super Normal Design. Des. J. 2019, 22, 589–599. [Google Scholar] [CrossRef]
  40. Ioannou, A.; Constantinou, V. Augmented reality supporting deaf students in mainstream schools: Two case studies of practical utility of the technology. In Interactive Mobile Communication Technologies and Learning: Proceedings of the 11th IMCL Conference; Springer International Publishing: Cham, Switzerland, 2018; pp. 387–396. [Google Scholar]
  41. Federici, S.; Meloni, F.; Borsci, S. The abandonment of assistive technology in Italy: A survey of users of the national health service. Eur. J. Phys. Rehabil. Med. 2016, 52, 516–526. [Google Scholar] [PubMed]
  42. Petrie, H.; Carmien, S.; Lewis, A. Assistive technology abandonment: Research realities and potentials. In Computers Helping People with Special Needs: 16th International Conference, ICCHP 2018, Linz, Austria, 11–13 July 2018, Proceedings, Part II 16; Springer International Publishing: Cham, Switzerland, 2018; pp. 532–540. [Google Scholar]
  43. Choi, J.E.; Ma, S.M.; Park, H.; Cho, Y.-S.; Hong, S.H.; Moon, I.J. A comparison between wireless CROS/BiCROS and soft-band BAHA for patients with unilateral hearing loss. PLoS ONE 2019, 14, e0212503. [Google Scholar] [CrossRef]
  44. de Jonge, D.; Aplin, T.; Larkin, S.; Ainsworth, E. The aesthetic appeal of assistive technology and the economic value baby boomers place on it: A pilot study. Aust. Occup. Ther. J. 2016, 63, 415–423. [Google Scholar] [CrossRef] [PubMed]
  45. Trist, E.L. The Evolution of Socio-Technical Systems; Ontario Quality of Working Life Centre: Toronto, ON, Canada, 1981; Volume 2. [Google Scholar]
  46. van Eijnatten, F.M. Developments in socio-technical systems design (STSD). In A Handbook of Work and Organizational Psychology; Psychology Press: London, UK, 2013; pp. 61–88. [Google Scholar]
  47. Maguire, M. Socio-technical systems and interaction design—21st century relevance. Appl. Ergon. 2014, 45, 162–170. [Google Scholar] [CrossRef]
  48. Sony, M.; Naik, S. Industry 4.0 integration with socio-technical systems theory: A systematic review and proposed theoretical model. Technol. Soc. 2020, 61, 101248. [Google Scholar] [CrossRef]
  49. Punch, J.L.; Hitt, R.; Smith, S.W. Hearing loss and quality of life. J. Commun. Disord. 2019, 78, 33–45. [Google Scholar] [CrossRef]
  50. Wang, S.M.; Chuan-Chuan Lin, J. The effect of social influence on bloggers’ usage intention. Online Inf. Rev. 2011, 35, 50–65. [Google Scholar] [CrossRef]
  51. Steuer, J.; Biocca, F.; Levy, M.R. Defining virtual reality: Dimensions determining telepresence. Commun. Age Virtual Real. 1995, 33, 37–39. [Google Scholar] [CrossRef]
  52. Davis, F.D. New Measures for Three User Acceptance Constructs: Attitude Toward Using, Perceived Usefulness, and Perceived Ease of Use. Student Thesis, University of Michigan, Ann Arbor, MI, USA, 1987. [Google Scholar]
  53. Sweeney, A.D.; Morrison, M.D.; Jarratt, D.; Heffernan, T. Modeling the constructs contributing to the effectiveness of marketing lecturers. J. Mark. Educ. 2009, 31, 190–202. [Google Scholar] [CrossRef]
  54. Lin, C.P.; Bhattacherjee, A. Extending technology usage models to interactive hedonic technologies: A theoretical model and empirical test. Inf. Syst. J. 2010, 20, 163–181. [Google Scholar] [CrossRef]
  55. Wilkes, R.E. A structural modeling approach to the measurement and meaning of cognitive age. J. Consum. Res. 1992, 19, 292–301. [Google Scholar] [CrossRef]
  56. Taylor, S.; Todd, P.A. Understanding information technology usage: A test of competing models. Inf. Syst. Res. 1995, 6, 144–176. [Google Scholar] [CrossRef]
  57. Batool, K.; Iqbal, M.N.; Mushtaq, R.; Shakeel, M. Effectiveness of Assistive Technology in Teaching Mathematics to the Students with Hearing Impairment at Primary Level. VFAST Trans. Educ. Soc. Sci. 2022, 10, 93–99. [Google Scholar]
  58. Bambacas, M.; Patrickson, M. Interpersonal communication skills that enhance organisational commitment. J. Commun. Manag. 2008, 12, 51–72. [Google Scholar] [CrossRef]
  59. Gugenheimer, J.; Plaumann, K.; Schaub, F.; Vito, P.D.C.S.; Duck, S.; Rabus, M.; Rukzio, E. The Impact of Assistive Technology on Communication Quality Between Deaf and Hearing Individuals. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, Portland, OR, USA, 25 February–1 March 2017; pp. 669–682. [Google Scholar]
  60. Sockalingam, R.; Holmberg, M.; Eneroth, K.; Shulte, M. Binaural hearing aid communication shown to improve sound quality and localization. Hear. J. 2009, 62, 46–47. [Google Scholar] [CrossRef]
  61. Reddy, C.K.A.; Shankar, N.; Bhat, G.S.; Charan, R.; Panahi, I. An Individualized Super-Gaussian Single Microphone Speech Enhancement for Hearing Aid Users with Smartphone as an Assistive Device. IEEE Signal Process. Lett. 2017, 24, 1601–1605. [Google Scholar] [CrossRef] [PubMed]
  62. López-Espejo, I.; Tan, Z.-H.; Jensen, J. Improved external speaker-robust keyword spotting for hearing assistive devices. IEEE/ACM Trans. Audio Speech Lang. Process. 2020, 28, 1233–1247. [Google Scholar] [CrossRef]
  63. Ganguly, A.; Küçük, A.; Panahi, I. Real-time smartphone application for improving spatial awareness of hearing assistive devices. In Proceedings of the 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, USA, 18–21 July 2018; pp. 433–436. [Google Scholar]
  64. Skehan, P. Processing perspectives on task performance. In Processing Perspectives on Task Performance; John Benjamins Publishing Company: Amsterdam, The Netherlands, 2014; pp. 1–278. [Google Scholar]
  65. Tavakoli, P.; Skehan, P. 9. Strategic planning, task structure and performance testing. In Planning and Task Performance in a Second Language; John Benjamins: Amsterdam, The Netherlands, 2005; pp. 239–273. [Google Scholar]
  66. Hilton, H. Oral fluency and spoken proficiency: Considerations for research and testing. Meas. L2 Profic. Perspect. SLA 2014, 27, 53. [Google Scholar]
  67. Niparko, J.K.; Marlowe, A. Hearing aids and cochlear implants. In Oxford Handbook of Auditory Science: The Ear; Oxford University Press: Oxford, UK, 2010; pp. 409–436. [Google Scholar] [CrossRef]
  68. Gao, Q.; Rau, P.-L.P.; Salvendy, G. Measuring perceived interactivity of mobile advertisements. Behav. Inf. Technol. 2010, 29, 35–44. [Google Scholar] [CrossRef]
  69. Arshad, M.; Akram, M.S. Social media adoption by the academic community: Theoretical insights and empirical evidence from developing countries. Int. Rev. Res. Open Distrib. Learn. 2018, 19, 244–262. [Google Scholar] [CrossRef]
  70. Abdullah, D.; Jayaraman, K.; Shariff, D.; Bahari, K.A.; Nor, N.M. The effects of perceived interactivity, perceived ease of use and perceived usefulness on online hotel booking intention: A conceptual framework. Int. Acad. Res. J. Soc. Sci. 2017, 3, 16–23. [Google Scholar]
  71. Jiarui, W.; Xiaoli, Z.; Jiafu, S. Interpersonal Relationship, Knowledge Characteristic, and Knowledge Sharing Behavior of Online Community Members: A TAM Perspective. Comput. Intell. Neurosci. 2022, 2022, 4188480. [Google Scholar] [CrossRef] [PubMed]
  72. Chan, T.J.; Yong, W.K.; Harmizi, A. Usage of WhatsApp and interpersonal communication skills among private university students. J. Arts Soc. Sci. 2020, 3, 15–25. [Google Scholar]
  73. Mittal, S.; Gera, R.; Batra, D.K. An evaluation of an integrated perspective of perceived service quality for retail banking services in India. Int. J. Bank Mark. 2015, 33, 330–350. [Google Scholar] [CrossRef]
  74. Jin, H.K.; Park, S.H.; Kang, J.E.; Choi, K.S.; Kim, H.A.; Jeon, M.S.; Rhie, S.J. The influence of a patient counseling training session on pharmacy students’ self-perceived communication skills, confidence levels, and attitudes about communication skills training. BMC Med. Educ. 2019, 19, 172. [Google Scholar] [CrossRef]
  75. Blood, G.W.; Blood, I.M.; Tellis, G.; Gabel, R. Communication apprehension and self-perceived communication competence in adolescents who stutter. J. Fluen. Disord. 2001, 26, 161–178. [Google Scholar] [CrossRef]
  76. Power, M.R.; Power, D.; Horstmanshof, L. Deaf people communicating via SMS, TTY, relay service, fax, and computers in Australia. J. Deaf Stud. Deaf Educ. 2007, 12, 80–92. [Google Scholar] [CrossRef]
  77. Pilling, D.; Barrett, P. Text communication preferences of deaf people in the United Kingdom. J. Deaf Stud. Deaf Educ. 2008, 13, 92–103. [Google Scholar] [CrossRef] [PubMed]
  78. Sexton, J. Empowering adolescents who are deaf and hard of hearing. N. Carol. Med. J. 2017, 78, 129–130. [Google Scholar] [CrossRef]
  79. Dawes, P.; Maslin, M.; Munro, K.J. ‘Getting used to’hearing aids from the perspective of adult hearing-aid users. Int. J. Audiol. 2014, 53, 861–870. [Google Scholar] [CrossRef] [PubMed]
  80. Backenroth, G.A.; Ahlner, B.H. Quality of life of hearing-impaired persons who have participated in audiological rehabilitation counselling. Int. J. Adv. Couns. 2000, 22, 225–240. [Google Scholar] [CrossRef]
  81. Khairani, A.; Ahmad, R.; Marjohan, M. Contribution of self image to interpersonal communication between students in the schools. J. Couns. Educ. Technol. 2019, 2, 65–70. [Google Scholar] [CrossRef]
  82. Rodriguez Mosquera, P.M.; Uskul, A.K.; Cross, S.E. The centrality of social image in social psychology. Eur. J. Soc. Psychol. 2011, 41, 403–410. [Google Scholar] [CrossRef]
  83. Lee, S.; Park, H.; Ahn, Y. The influence of tourists’ experience of quality of street foods on destination’s image, life satisfaction, and word of mouth: The moderating impact of food neophobia. Int. J. Environ. Res. Public Health 2020, 17, 163. [Google Scholar] [CrossRef]
  84. Li, H.; Lien, C.-H.; Wang, S.W.; Wang, T.; Dong, W. Event and city image: The effect on revisit intention. Tour. Rev. 2021, 76, 212–228. [Google Scholar] [CrossRef]
  85. Heffernan, E.; Coulson, N.S.; Henshaw, H.; Barry, J.G.; Ferguson, M.A. Understanding the psychosocial experiences of adults with mild-moderate hearing loss: An application of Leventhal’s self-regulatory model. Int. J. Audiol. 2016, 55, S3–S12. [Google Scholar] [CrossRef] [PubMed]
  86. Barak, A.; Sadovsky, Y. Internet use and personal empowerment of hearing-impaired adolescents. Comput. Hum. Behav. 2008, 24, 1802–1815. [Google Scholar] [CrossRef]
  87. Lin, C.-P.; Huang, H.-N.; Joe, S.-W.; Ma, H.-C. Learning the Determinants of Satisfaction and Usage Intention of Instant Messaging. CyberPsychol. Behav. 2008, 11, 262–267. [Google Scholar] [CrossRef]
  88. Bénabou, R.; Tirole, J. Self-confidence and personal motivation. Q. J. Econ. 2002, 117, 871–915. [Google Scholar] [CrossRef]
  89. Lubis, L.; Fazira, E. Connection Management Self-Concept and Social Support with Student Confidence. Nidhomul Haq: J. Manaj. Pendidik. Islam 2022, 7, 31–38. [Google Scholar] [CrossRef]
  90. Foustanos, A.; Pantazi, L.; Zavrides, H. Representations in Plastic Surgery: The Impact of Self-Image and Self-Confidence in the Work Environment. Aesthetic Plast. Surg. 2007, 31, 435–442. [Google Scholar] [CrossRef]
  91. Simsek, N.; Evli, M.; Uzdil, N.; Albayrak, E.; Kartal, D. Body Image and Sexual Self-confidence in Patients with Chronic Urticaria. Sex. Disabil. 2020, 38, 147–159. [Google Scholar] [CrossRef]
  92. Venkatesh, V.; Morris, M.G. Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Q. 2000, 24, 115–139. [Google Scholar] [CrossRef]
  93. Kim, H.-W.; Gupta, S.; Koh, J. Investigating the intention to purchase digital items in social networking communities: A customer value perspective. Inf. Manag. 2011, 48, 228–234. [Google Scholar] [CrossRef]
  94. Bispo, R.; Branco, V. Designing out Stigma: A New Approach to Designing for Human Diversity; European Academy of Design: Porto, Portugal, 2011. [Google Scholar]
  95. Stankov, L.; Lee, J.; Luo, W.; Hogan, D.J. Confidence: A better predictor of academic achievement than self-efficacy, self-concept and anxiety? Learn. Individ. Differ. 2012, 22, 747–758. [Google Scholar] [CrossRef]
  96. Hong, J.-C.; Hwang, M.-Y.; Tai, K.-H.; Tsai, C.-R. An Exploration of Students’ Science Learning Interest Related to Their Cognitive Anxiety, Cognitive Load, Self-Confidence and Learning Progress Using Inquiry-Based Learning with an iPad. Res. Sci. Educ. 2017, 47, 1193–1212. [Google Scholar] [CrossRef]
  97. Kim, H.-S.; Ahn, J.; No, J.-K. Applying the Health Belief Model to college students’ health behavior. Nutr. Res. Pract. 2012, 6, 551–558. [Google Scholar] [CrossRef] [PubMed]
  98. Chai, C.S.; Lin, P.Y.; Jong, M.S.y.; Dai, Y.; Chiu, T.K.F.; Huang, B. Factors Influencing Students’ Behavioral Intention to Continue Artificial Intelligence Learning. In Proceedings of the 2020 International Symposium on Educational Technology (ISET), Bangkok, Thailand, 24–27 August 2020; pp. 147–150. [Google Scholar]
  99. Shanahan, T.; Tran, T.P.; Taylor, E.C. Getting to know you: Social media personalization as a means of enhancing brand loyalty and perceived quality. J. Retail. Consum. Serv. 2019, 47, 57–65. [Google Scholar] [CrossRef]
  100. Wang, Y.-Y.; Wang, Y.-S.; Lin, H.-H.; Tsai, T.-H. Developing and validating a model for assessing paid mobile learning app success. Interact. Learn. Environ. 2019, 27, 458–477. [Google Scholar] [CrossRef]
  101. Huang, L.-T.; Chiu, C.-A.; Sung, K.; Farn, C.-K. A comparative study on the flow experience in web-based and text-based interaction environments. Cyberpsychol. Behav. Soc. Netw. 2011, 14, 3–11. [Google Scholar] [CrossRef]
  102. Khlaisang, J.; Songkram, N.; Huang, F.; Teo, T. Teachers’ perception of the use of mobile technologies with smart applications to enhance students’ thinking skills: A study among primary school teachers in Thailand. Interact. Learn. Environ. 2023, 31, 5037–5058. [Google Scholar] [CrossRef]
  103. Lam, C.; Campbell, K.S. Follow the Leader? The Impact of Leader Rapport Management on Social Loafing. Bus. Prof. Commun. Q. 2021, 84, 181–204. [Google Scholar] [CrossRef]
  104. Yang, H.; Yu, J.; Zo, H.; Choi, M. User acceptance of wearable devices: An extended perspective of perceived value. Telemat. Inform. 2016, 33, 256–269. [Google Scholar] [CrossRef]
  105. Rajeh, M.T.; Abduljabbar, F.H.; Alqahtani, S.M.; Waly, F.J.; Alnaami, I.; Aljurayyan, A.; Alzaman, N. Students’ satisfaction and continued intention toward e-learning: A theory-based study. Med. Educ. Online 2021, 26, 1961348. [Google Scholar] [CrossRef]
  106. Hong, J.-C.; Lin, P.-H.; Hsieh, P.-C. The effect of consumer innovativeness on perceived value and continuance intention to use smartwatch. Comput. Hum. Behav. 2017, 67, 264–272. [Google Scholar] [CrossRef]
  107. Deng, L.; Wei, W.; Chen, J. A Study on the Impact Mechanisms of Users’ Behavioral Intentions Towards Augmented Reality Picture Books for Adult Readers. Int. J. Hum. Comput. Interact. 2024, 1–18. [Google Scholar] [CrossRef]
  108. Hair, J.F.; Risher, J.J.; Sarstedt, M.; Ringle, C.M. When to use and how to report the results of PLS-SEM. Eur. Bus. Rev. 2019, 31, 2–24. [Google Scholar] [CrossRef]
  109. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  110. Henseler, J.; Ringle, C.M.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 2015, 43, 115–135. [Google Scholar] [CrossRef]
  111. Gold, A.H.; Malhotra, A.; Segars, A.H. Knowledge management: An organizational capabilities perspective. J. Manag. Inf. Syst. 2001, 18, 185–214. [Google Scholar] [CrossRef]
  112. Henseler, J.; Ringle, C.M.; Sinkovics, R.R. The use of partial least squares path modeling in international marketing. In New Challenges to International Marketing; Emerald Group Publishing Limited: Bingley, UK, 2009; Volume 20, pp. 277–319. [Google Scholar]
  113. Cohen, J. Statistical Power Analysis for the Behavioral Sciences; Lawrence Erlbaum: Hillsdale, NJ, USA, 1988; pp. 75–108. [Google Scholar]
  114. Eksvärd, S.; Falk, J. Evaluating Speech-to-Text Systems and AR-glasses: A study to develop a potential assistive device for people with hearing impairments. Student Thesis, Uppsala University, Uppsala, Sweden, 2021. [Google Scholar]
  115. Helvik, A.-S.; Jacobsen, G.; Svebak, S.; Hallberg, L.R.M. Hearing Impairment, Sense of Humour and Communication Strategies. Scand. J. Disabil. Res. 2007, 9, 1–13. [Google Scholar] [CrossRef]
  116. Barrenas, M.-L.; Holgers, K.-M. A clinical evaluation of the hearing disability and handicap scale in men with noise induced hearing loss. Noise Health 2000, 2, 67. [Google Scholar] [PubMed]
  117. de Miranda, R.S.; Shubert, C.O.; Machado, W.C.A. Communication with people with hearing disabilities: An integrative review. Rev. Pesqui. Cuid. Fundam. Online 2014, 6, 1695–1706. [Google Scholar] [CrossRef]
  118. Hines, J. Communication problems of hearing-impaired patients. Nurs. Stand. (Through 2013) 2000, 14, 33. [Google Scholar] [CrossRef]
  119. Bion, W.R. Attention and Interpretation; Jason Aronson: Lanham, MD, USA, 1995. [Google Scholar]
  120. Tajfel, H.; Turner, J.C. The social identity theory of intergroup behavior. In Political Psychology; Psychology Press: London, UK, 2004; pp. 276–293. [Google Scholar]
  121. Vicars, W.G. Is Being Deaf a Disability? Available online: https://www.lifeprint.com/asl101/topics/disability-deafness.htm (accessed on 2 February 2024).
  122. Faucett, H.A.; Ringland, K.E.; Cullen, A.L.; Hayes, G.R. (In) visibility in disability and assistive technology. ACM Trans. Access. Comput. (TACCESS) 2017, 10, 1–17. [Google Scholar] [CrossRef]
  123. Bandura, A. Self-efficacy: Toward a unifying theory of behavioral change. Psychol. Rev. 1977, 84, 191. [Google Scholar] [CrossRef]
Behavsci 14 00728 g001
Figure 1. Research model.
Figure 1. Research model.
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Figure 2. Results of path analysis. (* The level of significance is below 0.05).
Figure 2. Results of path analysis. (* The level of significance is below 0.05).
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Table 1. Operational definitions of constructs.
Table 1. Operational definitions of constructs.
ConstructOperational DefinitionSource
Function qualityThe completeness and quality of functions of AR smart glasses.Wang and Chuan-Chuan Lin [50]
Perceived interaction speedThe response speed of AR smart glasses as perceived by PHI.Steuer, Biocca and Levy [51]
Perceived ease of useThe ease of use of AR smart glasses as perceived by PHI.Davis [52]
Communication effectivenessThe effectiveness and quality of interactions and communication between PHI and others.Sweeney, Morrison [53]
Social imageThe views and respect that PHI receive from others.Lin and Bhattacherjee [54]
ConfidenceThe confidence of PHI that AR glasses can assist them in communication.Wilkes [55]
Behavioral intentionThe intention of PHI to use AR smart glasses as hearing aids.Taylor and Todd [56]
Table 2. Measurement scale of influencing factors of PHI using AR hearing assistant glasses.
Table 2. Measurement scale of influencing factors of PHI using AR hearing assistant glasses.
ConstructsItemsContentSource
Function qualityFQ1I feel that the speech-to-text accuracy of AR glasses is very high.Shanahan, Tran and Taylor [99], Wang, Wang [100]
FQ2I feel that the speech-to-text quality of AR glasses is high.
FQ3I believe that the information output from the AR glasses is reliable.
FQ4I believe the functionality quality of the AR glasses meets my requirements.
Perceived interaction speedPIS1I feel that the speech-to-text speed of AR glasses is very fast.Huang, Chiu [101]
PIS2I believe the process of speech-to-text with AR glasses is very smooth.
PIS3I believe the speech-to-text speed of AR glasses is almost synchronous with the speed of the other person’s speech.
PIS4I feel that the response speed of the AR glasses is fast when communicating with others.
Perceived ease of usePEU1Learning how to use AR glasses is easy for me.Khlaisang, Songkram [102]
PEU2Interacting with AR glasses doesn’t require much effort.
PEU3I can use AR glasses proficiently in communication.
Communication effectivenessCE1With the help of AR glasses, I communicate with others more easily and comfortably.Sweeney, Morrison [53], Lam and Campbell [103]
CE2With the assistance of AR glasses, I can communicate better with others.
CE3AR glasses help me understand others more effortlessly.
CE4With the assistance of AR glasses, I can communicate with others smoothly and without barriers.
Social imageSI1By using AR glasses, I have shed the image of being hearing-impaired. Yang, Yu [104]
SI2By using AR glasses, others see me as a normal person.
SI3Using AR glasses gives others the impression that I am a regular individual.
ConfidenceCO1With the help of AR glasses, I now have the confidence to handle the entire communication process.Hong, Hwang [96]
CO2Compared to before, with the help of AR glasses, I believe my communication performance is better.
CO3Compared to before, with the assistance of AR glasses, I will communicate with others more confidently.
Behavioral intentionBI1I am willing to use AR glasses as my hearing assistance device.Rajeh, Abduljabbar [105], Hong, Lin and Hsieh [106]
BI2I would recommend AR glasses to my hearing-impaired friends.
BI3I will continue to use AR glasses in the future.
Table 3. Demographic information of the respondents.
Table 3. Demographic information of the respondents.
CategoryGroupNumberPercentage
GenderMale7338.624%
Female11661.376%
Age<18126.349%
18–3010052.910%
31–403619.048%
41–502412.698%
51–60147.407
>6031.587
EducationHigh school or technical secondary school and below5529.101%
junior college6333.333%
Undergraduate 6534.392%
Graduate and above63.175%
Degrees of hearing impairmentMild10756.614%
Moderate7740.741%
Severe52.646%
Table 4. Loadings, AVE, composite reliability, and Cronbach’s alpha.
Table 4. Loadings, AVE, composite reliability, and Cronbach’s alpha.
ConstructsItemsLoadingsCronbach’s AlphaComposite Reliability (rho_a)Composite Reliability (rho_c)AVE
Function qualityFQ10.8520.8660.8690.9090.713
FQ20.844
FQ30.834
FQ40.847
Perceived
interaction speed		PIS10.8450.870.8740.9110.72
PIS20.868
PIS30.832
PIS40.848
Perceived ease of usePEU1
PEU2
PEU3		0.8390.790.7970.8770.703
0.824
0.853
Communication effectivenessCE10.8510.8680.8680.910.717
CE20.86
CE30.843
CE40.832
Social imageSI10.8250.8330.8380.90.75
SI20.903
SI30.869
ConfidenceCO10.8760.8430.8450.9050.761
CO20.881
CO30.861
Behavioral intentionBI10.8540.8670.8690.9190.791
BI20.897
BI30.915
Table 5. Discriminant validity: Fornell–Larcker criterion.
Table 5. Discriminant validity: Fornell–Larcker criterion.
FQPISPEUCESICOBI
FQ0.844
PIS0.7710.848
PEU0.6090.6060.839
CE0.7080.7050.7330.847
SI0.5930.5930.5710.6850.866
CO0.5890.5690.6160.7070.7240.873
BI0.5890.5860.6450.7630.6830.7480.889
Note: Bold numbers is the square root of the AVE values for each construct.
Table 6. Discriminant validity: heterotrait/monotrait ratio (HTMT).
Table 6. Discriminant validity: heterotrait/monotrait ratio (HTMT).
FQPISPEUCESICOBI
FQ
PIS0.887
PEU0.7310.721
CE0.8120.8080.878
SI0.6960.6950.6980.805
CO0.6840.6600.7550.8250.861
BI0.6750.6720.7720.8790.8010.875
Table 7. Results of R2 and Q2.
Table 7. Results of R2 and Q2.
ConstructR2Q2
Communication effectiveness0.6690.472
Social image0.4690.348
Confidence0.6080.454
Behavior intention0.6020.471
Table 8. Model fit indices.
Table 8. Model fit indices.
IndicesEstimated Model
SRMR0.082
d_ULS2.007
d_G0.598
Chi square648.539
NFI0.804
Table 9. Path coefficients and the results of the significance tests.
Table 9. Path coefficients and the results of the significance tests.
HypothesisPathStd Betat Statisticsp ValuesVIFResults
H1FQ → CE0.2563.3290.00012.674Support
H2PIS → CE0.2503.4490.00012.655Support
H3PEU → CE0.4267.6180.00001.715Support
H4CE → CO0.3986.2980.00001.882Support
H5CE → SI0.68516.1940.00001.000Support
H6SI → CO0.4517.3370.00001.882Support
H7SI → BI0.2963.6830.00002.101Support
H8CO → BI0.5347.3140.00002.101Support
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Deng, L.; Chen, J.; Li, D. Factors Influencing Intentions of People with Hearing Impairments to Use Augmented Reality Glasses as Hearing Aids. Behav. Sci. 2024, 14, 728. https://doi.org/10.3390/bs14080728

AMA Style

Deng L, Chen J, Li D. Factors Influencing Intentions of People with Hearing Impairments to Use Augmented Reality Glasses as Hearing Aids. Behavioral Sciences. 2024; 14(8):728. https://doi.org/10.3390/bs14080728

Chicago/Turabian Style

Deng, Liyuan, Jiangjie Chen, and Dongning Li. 2024. "Factors Influencing Intentions of People with Hearing Impairments to Use Augmented Reality Glasses as Hearing Aids" Behavioral Sciences 14, no. 8: 728. https://doi.org/10.3390/bs14080728

APA Style

Deng, L., Chen, J., & Li, D. (2024). Factors Influencing Intentions of People with Hearing Impairments to Use Augmented Reality Glasses as Hearing Aids. Behavioral Sciences, 14(8), 728. https://doi.org/10.3390/bs14080728

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