A Study on the Sound Therapy Interaction Design to Alleviate Homesickness: The HomeSeek App among Chinese Users

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The sound therapy interaction design model proposed in this study contributes to the medical field from a design perspective by suggesting new therapeutic methods for coping with homesickness to be learned and applied. For the practical aspect, it can be widely applied to the development of other products to help people cope with homesickness more easily and have a better therapy experience, which psychologically closes the distance between people in different places and their homes and prevents nostalgia from developing into more serious psychological problems to some extent.

Abstract

Research in the field of psychological health care has confirmed that chronic homesickness can exacerbate emotional problems. However, there is a lack of diverse products in the design field that can effectively address the issue of alleviating homesickness. This study explores how interaction design can mitigate homesickness-related anxiety while delivering a good user experience, from an application-driven perspective. An inclusive design approach was adopted. Firstly, an online survey was conducted in China through social media platforms (WeChat and websites), and 323 responses were analyzed to examine Chinese preferences for sounds that alleviate homesickness and the influence of various characteristics on the perception of hometown sounds. Secondly, personas were created to capture user needs. Based on regional differences, local sound characteristics, and adaptation to various audience backgrounds, this study examined the effects of these sounds on alleviating homesickness across different scenarios and proposed a sound therapy design model. The practical application of this model was demonstrated through the HomeSeek app, which provides personalized therapeutic experiences. Finally, an application usability test was conducted. The findings indicated that 92.5% of participants were satisfied with the homesickness therapy experience, demonstrating its effectiveness in alleviating homesickness and providing strong support for the research model.

1. Introduction

With the development of globalization and the digital era, more and more people are willing to study, work, and live away from home. They leave their hometowns to seek better personal development in other cities or countries [1]. One of the negative effects of leaving a hometown is homesickness, the classic symptom of which is the recurring longing for home and the desire to return to it [2]. Homesickness, also known as nostalgia, is the distress experienced when separated from home due to personal or external factors [3]. Home means physical, social, and emotional comfort. People miss their homes for different reasons, such as activities, family, feelings, and places, among others [4]. Almost everyone experiences homesickness during their life, regardless of age [3]. What is more, chronic homesickness can lead to negative psychological impacts and mental health disorders. Previous studies by Baisac et al. and Sun et al. highlighted that homesick students experienced a range of physical symptoms such as headaches, fatigue, and difficulty concentrating [5,6]. Students with stronger family ties were at higher risk of experiencing severe homesickness, and chronic homesickness led to long-term emotional stress and impaired academic performance [7]. Meanwhile, Van Tilburg stated that homesickness is also associated with serious health problems in both adults and the elderly. People experiencing homesickness often reported higher levels of stress, anxiety, and depression, which directly impacted their overall well-being [5,8]. This phenomenon has become increasingly prevalent in today’s global environment. These observations emphasize the importance of exploring ways to help relieve people of homesickness.

Various methods have been proposed to address homesickness in different fields. In the medical field, experts suggest long-term treatment and early intervention for homesickness, such as consulting a mental health professional or adopting a healthy lifestyle to ease homesickness [3,9]. In the technical field, digital tools (e.g., video chat or phone calls) can offer social contact that can reduce homesickness and the psychological distance from home [10]. A study by Wadley et al. revealed that international students sometimes use music streaming services to deal with the emotional and psychological challenges of living abroad [11]. This is because homesickness is not only about missing people but also about missing the place and the experiences [12]. Compared with communication, ambient sounds convey a rich image of the happenings around us, especially natural sounds, which provide a continuous awareness around us [13]. Meanwhile, not everyone is comfortable expressing their emotions or seeking help from others, as some people may be introverted or prefer to cope with negative feelings by themselves [14]. Sound or music therapy can also play a positive role in the treatment of this group of individuals. The research conducted by Athina Tsirigoti and Maria Georgiadi investigated the efficacy of music therapy programs in enhancing social communication skills among children with Autism Spectrum Disorder (ASD) [15]. In the design field, the Human–Computer Interaction offers a potential solution for this group by providing personalized interactive sound therapy that does not require social interaction. Recent studies have also explored the application of artificial intelligence in enhancing the accessibility of music therapy for emotional regulation and mental health, thereby enabling personalized and adaptive therapeutic experiences [16]. Zhao et al.’s research demonstrated that mobile applications can effectively alleviate symptoms of post-traumatic stress disorder (PTSD) [17]. Additionally, the use of AI in sound therapy has been shown to help reduce loneliness and anxiety among elderly individuals living alone, thus improving their mental health outcomes [18].

With technological advancements, emerging technologies are increasingly being applied to sound therapy, driving innovation and development in this field. Previous research explored the use of emerging technologies to treat negative emotions and psychological issues. As homesickness becomes a global trend and the impact of prolonged homesickness on mental health becomes more severe, there remains a lack of design research focused on using such technologies to help mitigate homesickness. Compared with previous studies, this research aims to explore, from the perspective of interaction design, how sound therapy can offer a more personalized approach to alleviate homesickness among the Chinese population as well as enhance the user therapy experience.

China is the fourth-largest source of international migrants, with more than 10 million people leaving their hometowns each year, as stated by the World Migration Report 2022 [19]. Homesickness is not only transnational, but it also occurs for those who relocate within China. It is not only limited to the young generation, but is it also experienced by various groups of people [7,20]. Chinese culture emphasizes the importance of family and kinship, and many Chinese people have a strong sense of belonging to their families and hometowns. However, traveling back home can be challenging because of the vastness of China and the high costs and time involved. Therefore, many people resort to phone calls and video calls to maintain contact with their families. Meanwhile, the number of mobile phone users in China has been growing rapidly, reaching 10.47 billion in August 2022 [21]. In this study, we chose to design a mobile phone app as a product output form to explore how design can help alleviate homesickness.

Sound can heal emotions, but everyone has different feelings and memories of home. This research explores whether people can use sound symbols to represent their memories of their homes and alleviate their homesickness. Specifically, we address the following three questions: (1) what kind of sound can alleviate homesickness for Chinese people, (2) how can interaction design be applied to help people cope with homesickness, and (3) why is sound therapy interaction design effective? In this study, we first conducted an online questionnaire with 322 participants. After summarizing the data, we analyzed it by using ANOVA, with the aim of obtaining an objective analysis of the sound data (as shown in

Table 1. A summary of the basic information provided by participants in the questionnaire (n = 323).

Variables		Value (n)
Age	18–25	80
	26–40	129
	41–56	70
	≥57	44
Gender	Female	185
	Male	138
Leaving hometown now	Yes	205
	No	118
Reason of leaving hometown	Self-development (study/work)	198
	The pandemic disease (COVID-19)	21
	Move house (marriage...)	104
Living status	Live alone	95
	Live with families	157
	Live with friends	71
Hometown type	Bustling city	82
	Generic city	131
	Coastal city	66
	Countryside	44

,

Table 2. Common sounds of different hometowns (n = 323).

Sounds Type	Scores (S-(M))	Sounds Type	Scores (S-(M))
Bustling City		Coastal City
City street (e.g., car, bus, bicycle)	228 (2.78)	Sound of sea (e.g., waves, wind)	187 (2.83)
Crowded people in the street	183 (2.23)	Seagulls crying	134 (2.03)
Fireworks	196 (2.39)	Firecrackers (e.g., marriage)	146 (2.21)
Cicadas in summer	191 (2.32)	Fireworks	144 (2.18)
Gentle pet (e.g., cat, dog)	183 (2.23)	Cooking food (e.g., meat, hotpot)	140 (2.12)
Early morning with birdsong	183 (2.23)	Gentle pet (e.g., cat, dog)	125 (1.89)
Cooking food (e.g., meat, hotpot)	194 (2.37)	Early morning with birdsong	128 (1.93)
Cheers (e.g., concert, game)	177 (2.16)	Firewood burning	130 (1.97)
Generic City		Countryside
City street (e.g., car, bus, bicycle)	405 (3.09)	Sound of rural life (e.g., birdsong)	136 (3.09)
A tractor working	288 (2.20)	Cave (e.g., sound of water drops, echo)	84 (1.91)
Early morning with birdsong	322 (2.46)	Firewood burning	92 (2.09)
Fireworks	395 (3.02)	Wind blowing the leaves	95 (2.16)
Cooking food (e.g., meat, hotpot)	327 (2.50)	Streamlet	86 (1.95)
Gentle pet (e.g., cat, dog)	327 (2.50)	Animal sounds (e.g., dog barking, cow)	97 (2.20)
Cicadas in summer	401 (3.06)	Firecrackers (e.g., marriage)	100 (2.27)
Passing train	300 (2.29)	Cooking food (e.g., meat, hotpot)	87 (1.98)

, and

Table 3. The variance in the different sounds in the four cities.

Sounds Type	n	Mean	Sounds Type	n	Mean
Bustling city (p = 0.022)			Coastal city (p < 0.001)
City street (e.g., car, bus, bicycle)	82	2.78	Sound of sea (e.g., waves, wind)	66	2.83
Crowded people in the street	82	2.23	Seagulls crying	66	2.03
Fireworks	82	2.39	Firecrackers (e.g., marriage)	66	2.21
Cicadas in summer	82	2.33	Fireworks	66	2.18
Gentle pet (e.g., cat, dog)	82	2.23	Cooking food (e.g., meat, hotpot)	66	2.12
Early morning with birdsong	82	2.23	Gentle pet (e.g., cat, dog)	66	1.89
Cooking food (e.g., meat, hotpot)	82	2.37	Early morning with birdsong	66	1.94
Cheers (e.g., concert, game)	82	2.16	Firewood burning	66	1.97
Generic city (p < 0.001)			Countryside (p < 0.001)
City street (e.g., car, bus, bicycle)	131	3.09	Sound of rural life (e.g., birdsong)	44	3.09
A tractor working	131	2.20	Cave (e.g., sound of water drops, echo)	44	1.90
Early morning with birdsong	131	2.46	Firewood burning	44	2.09
Fireworks	131	3.02	Wind blowing the leaves	44	2.16
Cooking food (e.g., meat, hotpot)	131	2.50	Streamlet	44	1.95
Gentle pet (e.g., cat, dog)	131	2.50	Animal sounds (e.g., dog barking, cow)	44	2.20
Cicadas in summer	131	3.06	Firecrackers (e.g., marriage)	44	2.27
Passing train	131	2.29	Cooking food (e.g., meat, hotpot)	44	1.98

), and filtered out key information for app development. Then, we used a persona approach to analyze the needs of different users.

Based on the results of the data analysis and user requirements, the HomeSeeK app was developed to help Chinese people alleviate homesickness. The HomeSeek application provides a new way for people to access therapy. It allows people to access therapy anytime and anywhere, making it easier and more comfortable. In addition, this study also conducted a user usability test of the app and collected user feedback.

2. A Theoretical Model

2.1. Inclusive Design

Inclusive design is a user-centered design approach that acknowledges the diversity and uniqueness of populations [22]. The Inclusive Design Research Centre (IDRC) defines inclusive design as “design that considers the full range of human diversity with respect to ability, language, culture, gender, age and other forms of human difference” [23]. Inclusive design aims to understand the differences in user functionality, needs, and expectations and to develop products that accommodate as much diversity as possible to respond to demographic variation [24]. To ensure the effectiveness of sound therapy for homesickness, the diverse sound preferences of different people need to be taken into account. This study classifies people based on their complex relationship with home. We consider factors such as age, gender, migration status, reason for migration, and current residence. Moreover, we incorporate China’s geographical diversity as a novel dimension to examine the sound preferences of people from different regions. This research enriches the classification of inclusive design.

2.2. Sound Therapy Model for Homesickness

Music therapy is widely applied in various fields, especially as a component of multi-modal therapy in psychiatry [25]. Music therapy in psychiatry adopts a cognitive behavioral approach, addressing patients’ needs by stimulating their musical responses. The core mechanism of music therapy is that, first, the patient’s target behaviors are evaluated, and the need factors and risk factors are contrasted with the main symptoms. Second, the music therapist creates musical situations to elicit the patient’s behavioral and emotional responses. Third, music is employed to induce behavioral changes in the patient. Figure 1 illustrates the treatment cycle used by music therapists in cognitive behavioral music therapy in psychiatry, which is highly effective in altering the behavior of psychiatric patients. The success of the music therapy process depends on the therapist’s awareness and utilization of the neurological and physiological effects of music. The essence of music therapy is that the music therapist must select appropriate music to create scenarios that elicit emotional responses from the patient. The intensity of these responses can be amplified by the neurophysiology arousal responses in the patient’s brain [26].

Homesickness is generally considered a psychological condition and belongs to the field of psychiatry. While it can have physical symptoms, such as sleep disturbances or headaches, these are typically secondary to the emotional and mental distress caused by homesickness [2,27]. Therefore, the core mechanisms of the music therapy model can also be analyzed and applied to homesickness therapy. The first step is to evaluate the personal background and needs of the homesick person to achieve a good effect of sound therapy. The second step is to use sound to create a scene that evokes the person’s hometown and memories. Unlike cognitive therapy for psychiatric disorders, homesickness is a common psychological issue, and people can alleviate homesickness and prevent psychological problems through daily self-intervention. Moreover, for the sound selection of homesickness treatment, music is not the only sound component, as there are representative sounds of the hometowns in different regions. By integrating the therapeutic model in Figure 1 with the design process of interaction design, we developed a sound therapy interaction model for homesickness (Figure 2), which can serve as a theoretical basis for the interaction design of homesickness therapy. Based on this, we investigated the practical application and application effect of this model.

3. Methods

A design should focus on user needs and also take into account issues such as technology and product usability to ensure that the proposed solutions are both desirable and feasible [27]. To obtain valid research results and design solutions, we used the following three methods: (1) an online survey, (2) prototype design, and (3) user usability testing.

3.1. Online Survey

This study used a purposive quantitative questionnaire (described as an investigation into people’s homesickness factors). We determined the sample quantities by collecting as many responses as possible within a month. Then, we used purposive sampling to recruit interviewees for user needs assessment (described as a persona) and usability testing from the sample quantities. The requirements of the participants included the following: being as diverse as possible in age groups, having no hearing impairment, being away from home, being from different cities, owning a smartphone, being willing to install HomeSeek on the smartphone, and being able to communicate well. Participation in this research was voluntary.

The Influence of Various Factors on Homesickness among Chinese People

People’s memories of their hometowns are influenced by their diverse backgrounds, which may affect their preferences for hometown sounds. To explore the factors that impact the perception of hometown sounds and to examine the relationship between different sounds and the degree of homesickness, we conducted an online survey that was spread widely on social media (WeChat and a website). Some statistical experts suggest that the data range should be 5 to 10 times the number of scale items [28]. This questionnaire had 14 multiple-choice questions and a total of 323 participants, so the sample size was valid (Table 1).

People from different cities have different memories of their hometowns because of the obvious differences among Chinese cities. Based on the geographical characteristics of China (long coastline, many coastal cities) [29] and population migration patterns (more workers migrating, significant rural-to-urban migration) [30,31], we classified cities into four types as follows: metropolitan areas, general cities, coastal cities, and countryside. We conducted interviews with individuals from different types of cities to collect representative sounds of their hometowns. Based on the interview results, we provided the participants with eight representative hometown sounds from each of the four city types. Table 1 lists the representative sounds of various cities in China. All the participants heard ASMR sounds, which can enhance the user’s sense of immersion and experience [32]. Given the individual differences among those experiencing homesickness, to further investigate whether people with different characteristics experience different levels of homesickness in response to different sounds, we asked participants to answer six questions (age, gender, hometown, living status, whether they had left their hometowns, and the reasons for leaving their hometowns), as shown in Table 2. Table 2 presents the demographic information of the participants, showing that over 60% had left their hometowns.

After answering the six questions, according to the choice of hometown, the respondents listened to the representative sounds of their hometowns. Following each sound, the participants rated the extent to which the sound reminded them of their hometowns (“How much does it remind you of your hometown when you hear this sound?”). The rating scale ranged from 1 (a little) to 5 (very much). As shown in Table 2, these ratings were used as dependent variables to determine which sounds most strongly evoked a sense of home in the participants. Finally, to assess whether different characteristics influenced the results of sound scores, we conducted a multi-factor ANOVA based on the data collected as independent variables (age, gender, living status, whether they had left their hometowns, and the reasons for leaving their hometowns). The goal was to identify which independent variables affected the sound result, thereby enabling the provision of accurate hometown sounds to users.

3.2. Prototype Design

3.2.1. Persona

We adopted the persona approach, where a fictional person is constructed to represent the majority of users [33], and we designed and developed the product around this avatar. Four people with different backgrounds and hometowns were selected from the questionnaire participants and interviewed as the fictional user profile. The interviews covered basic questions about the participants’ backgrounds, including age, occupation, hometown, and residence status. We also asked the participants about their psychological state and experience using other digital apps, which indirectly revealed the user needs and requirements for the application. To identify the user requirements for the application’s functionality and to improve the design, we conducted a persona analysis. Figure 3 summarizes the four different personas.

Figure 3 shows that older people experienced more homesickness than younger people because the lifestyle in new cities was different from their hometowns, and this caused them to feel uncomfortable. Moreover, they were separated from their relatives and friends, so they were prone to feel lonely. Therefore, they often recalled the past and wished to return to their hometowns. Younger people faced a lot of pressure and had a more intense mental state. Under these circumstances, they were more likely to feel homesick.

We also found that older people had lower adaptability to complex digital products than younger people. P1 is a 71-year-old man who prefers a product with simple functions and easy-to-understand features. P4 is a 53-year-old man who wants a product with simple operations and does not require much time to learn. In contrast, the younger group is more inclusive of the product’s functionality, and they care more about the product’s experience and professionalism. Because young people live a fast-paced life and need to cope with various problems, they do not have much patience and time to learn about the product. Therefore, they need a product that can be used quickly and effectively to help them relieve their problems.

3.2.2. Interaction Design for Homesickness Sound Therapy

Interaction design is a technique that aims to make a product user-friendly and efficient by understanding the needs and expectations of the user, as well as their psychological and behavioral traits when interacting with the product. Considering that cell phones are essential in the daily lives of Chinese people, we chose a cell phone product as an interaction tool to alleviate homesickness and developed an app as the final output form.

Based on the user pain points and needs analyzed from the user research, the application’s concept structure was carried out. Adobe XD (Version: 45.0.62) software was employed to create a prototype of the HomeSeek app at this stage. This software enables the creation of interactive prototypes that can be tested rapidly before developing the app [34]. After building the interactive prototype, it can be shared with interested parties to obtain feedback on the user experience and facilitate the app’s development.

3.3. Usability Test of the HomeSeek App

A total of 40 users were invited to evaluate the usability of HomeSeek, including people who left their hometowns and product managers. We imported the Adobe Xd file into Modao software (Version: v1.3.6), which created a link and shared the app prototype with the participants. The participants were asked to use the app prototype independently and provide feedback. We classified HomeSeek’s usability test results into the following three categories based on the difficulty of task completion: “easy to complete”, “completed with difficulty”, and “failed to complete”, and collected feedback for each function. “Easy to complete” means the tester could use the app without any assistance. “Completed with difficulty” means the tester needed some assistance to use the app. “Failed to complete” means the tester could not use the app even with assistance [35].

4. Results

This study performed an analysis of the data collected from the questionnaire to examine the effects of different sounds on homesickness among users. Moreover, it explored other factors that might influence sound outcomes to ensure a more accurate sound solution for the HomeSeek app. Based on the data results and user requirements, the authors designed the functions and interface of the app systematically and evaluated the usability of the HomeSeek app. The aim of this application was to use sound therapy interaction design as an approach to help alleviate the users’ homesickness.

4.1. Theoretical Basis of Factors Affecting Sound

We employed the ANOVA method to examine the impact of various factors on the selected hometown sounds. We sequentially analyzed the influence of different cities and different sounds on homesickness, as well as different characteristics of people that affected the perception of hometown sounds. The final analysis results serve as a theoretical basis for the homesickness therapy provided by the application.

4.1.1. City Impact

First, we examined the variability in homesickness across cities. We performed an analysis of variance (ANOVA) on the homesickness scores of different cities (Figure 4). The results showed that the generic city had the highest score (2.64) and differed significantly from the scores of the other three cities. (M difference between the generic city and bustling city = 0.3, p < 0.001; M difference between the generic city and coastal city = 0.49, p < 0.001; M difference between the generic city and countryside = 0.43, p < 0.001). This suggested that people from a generic city were more prone to homesickness in China. Because of the urbanization trend in China, many people choose to move to big cities or abroad for education or employment, as they offer better academic and career opportunities.

4.1.2. Sound Impact

Next, we examined the variability in different sounds within the same city as shown in Table 3. Our ANOVA for the different sounds revealed that the sounds in the four cities were all different (${\mathrm{p}}_{\mathrm{b}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{l}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{c}\mathrm{i}\mathrm{t}\mathrm{y}}=0.02,{\mathrm{p}}_{\mathrm{c}\mathrm{o}\mathrm{a}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{c}\mathrm{i}\mathrm{t}\mathrm{y}},{\mathrm{p}}_{\mathrm{g}\mathrm{e}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{c}\mathrm{i}\mathrm{t}\mathrm{y}},{\mathrm{p}}_{\mathrm{c}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{y}\mathrm{s}\mathrm{i}\mathrm{d}\mathrm{e}}<0.001$). The “city streets” sound (the sound of people talking and cars) had the highest score in the bustling city, with a score of 2.78, which was significantly higher than the scores of the other four sounds (crowded, docile kittens, Kamakura early morning, and stadium cheers), while there were no significant differences in the scores among the remaining three sounds. The “walk under the sea” sound (sea bubbles and sea sounds) had the highest score in the coastal city, with a score of 2.78, which was significantly higher than the scores of other sounds. The generic city had three sounds with high scores, namely, “city streets”, “fireworks”, and “summer cicada chirps”. “City streets” had the highest score of 3.09, while “summer cicada chirps” had the second highest score of 3.06. The “idyllic life” sound (the sound of cows, dogs, and birdsong) had the highest score in the countryside, with a score of 3.09, which was significantly higher than the scores of the other sounds. These results indicated that people were most sensitive to nature soundscapes that were characteristic of their hometowns; for example, people whose hometowns were in cities were more sensitive to noisy street sounds, as well as bus and bicycle sounds. Unlike music, nature soundscapes are unprocessed. Nature soundscapes can help listeners relax more easily, reduce stress, and, to some extent, improve focus by allowing them to immerse themselves in the environment conveyed by the sounds, thereby bringing them into the associated context [13,36,37,38]. Therefore, in the app’s sound scheme, we provided users with representative sounds of their hometowns. For instance, people whose hometowns were in the countryside were most sensitive to various bird sounds, so we offered the sound of birds chirping in the app.

4.1.3. Preferences Impact

Finally, we investigated the variability in the different characteristics of the participants who completed the questionnaire. We collected data on gender, age, whether or not they had left their hometowns, why they had left their hometowns, and who they were currently living with. We then conducted a multi-factor ANOVA to investigate the effect of different characteristics on the results of sound scores.

As shown in

Table 4. The variance in the other aspects of the four cities.

	Variable	p Value		Variable	p Value
Bustling city	Age	0.0004	Coastal city	Age	0.2186
	Gender	0.0111		Gender	0.2991
	Whether to leave hometown	0.2128		Whether to leave hometown	0.6044
	Reason for leaving hometown	0.1082		Reason for leaving hometown	0.8367
	Residence status	0.0127		Residence status	0.3328
Generic city	Age	0.0000	Countryside	Age	0.5017
	Gender	0.4521		Gender	0.7477
	Whether to leave hometown	0.0005		Whether to leave hometown	0.4292
	Reason for leaving hometown	0.0078		Reason for leaving hometown	0.0035
	Living status	0.0000		Living status	0.1768

, the different characteristics also exhibited large variability among cities. For the bustling city, age, gender, and residence status had a significant effect on homesickness scores (p < 0.05); for the coastal city, none of the characteristics had a significant effect; for the generic city, age, whether they left home or not, the reason for leaving home, and residence status had significant effects on homesickness scores (p < 0.05); and for the countryside, the reason for leaving home had a significant effect on homesickness scores (p < 0.05). As a result, for the characteristics that were found to be significant, we designed age, gender, and other factors as question filter items in the app for users to answer to ensure the accuracy of the provided sound. Although there were no significant factors in the coastal city, we still asked people in a coastal city to answer the above questions in the app for accuracy.

4.2. Interaction Design Output—The HomeSeek App

4.2.1. App Development Conceptualization

Based on the results of the data analysis and user requirements, a concept map was created to organize the optimal logical structure of the homesickness sound therapy functions (Figure 5). The concept map illustrates the basic logic of the app. When users begin to use the application, they need to enter their basic information first, including gender, age, hometown, living status, and reasons for leaving their hometowns. Once the users have entered their basic information, the sound therapy process starts.

The app has two types of functions as follows: a fundamental function and an advanced function. The basic function is designed for users of any age. When the user finishes entering his or her basic information, the system will provide a matching sound based on the big data analysis. This process only includes a sound therapy function that can basically meet the sound homesickness therapy needs of all user groups. The advanced function is designed for users who have higher expectations for product functionality and a strong learning ability. Users can add sound elements based on their own preferences or record their favorite sounds, thus creating a personalized sound solution and achieving the inclusive design of product functionality. Moreover, users can activate the VR view function to have an immersive experience. The VR view is an advanced feature because VR technology, such as VR glasses, has become mature and widely used in daily life. VR technology can offer users the experience of returning to their hometowns, and together with sound therapy, it can help people reduce their homesickness more effectively.

4.2.2. App User Interface

Based on the design framework of the HomeSeek app, we developed a high-quality homesickness-coping app that satisfies users’ expectations at every stage of the development process. Therefore, we adopted a simple and intuitive interface design approach to ensure that the app is easy to understand and use. This will effectively reduce the learning time and operation error rate of the users, and it is also friendly for elderly and middle-aged people. In addition, we considered the user adoption and user experience of different groups of people when designing the app’s features and functions.

Figure 6 and Figure 7 illustrate the user interface design of the app. The theme color of the app is blue–green. According to color psychology, blue–green represents calmness, which can alleviate anxiety. Previous studies have revealed that color may influence brain waves and that blue induces calmness. When people are in a blue environment, their pulses slow down, and their emotions become gentler. Green is the color of nature, restful and soothing. It has strong healing powers, which is one of the reasons why it is the predominant color of hospital decor. Green light reduces stress, dilates capillaries, stimulates endocrine glands, and alleviates insomnia. The most relaxing and calming color in the spectrum is pale green [39].

Pages (a) to (h) in Figure 6 are fundamental functions. Page (a) is the login screen of the app. After users log in, they are directed to the basic information input pages, as shown on pages (b) to (f). Page (b) is the hometown selection page, page (c) is the gender selection page, page (d) is the age selection page, page (e) is the living status selection page, and page (f) is the reason for leaving a hometown selection page. After answering one question at a time, the user automatically moves to the next question. Once the user completes the basic information selection, the app jumps to the sound therapeutic pages (g)–(i). On page (g), there is a “Start” button, which means ready to start sound therapy. After the user clicks the “Start” button, the app turns to page (h), which is the volume adjustment page. On this page, users can adjust the volume to their comfortable level. The user clicks the “done” button after adjusting the volume. Then, the page jumps to (i), where the user hears the ASMR sound solution offered by the app.

Pages (i) to (m) in Figure 7 are advanced functions. On page (i), users are shown an image related to the sound on the upper portion of the interface, and they can click the “player” button if they want to see the image. It is a wide-angle image, and users can adjust the picture view, which has a better effect on homesickness therapy, on page (j). At the same time, users can upload the images they like, such as their hometown memories. When users are at home, they can have a more immersive experience if they use VR glasses. Users can also set a timer for the sound. When users click the “+” button, they are directed to the “Sound Gallery” page. Under this function, users can customize other favorite sound elements based on the sounds provided by the app, from page (k) to (m). The “Sound Gallery” categorizes sound factors into four types based on the city types and provides various representative sounds for each type, such as the sound of springs and caves in the countryside. The user can select up to three sound elements simultaneously and adjust the volume level of each sound individually. The icon of the selected sound element changes its color from gray to green. To switch to another sound, the user needs to deselect the current sound by clicking on its icon, which changes its color back to gray, and then choose a new sound. At the same time, users can also record their favorite sounds.

4.3. User Test and Feedback

To design an effective application, it was necessary to involve the end user (the homesick person) [40]. In terms of user testing (Figure 8), HomeSeek includes fundamental and advanced function testing, with fundamental function testing consisting of four parts as follows: information selection, therapeutic preparation, volume control, and sound therapeutic. The advanced function testing includes VR viewing, adding new sound elements, and changing other sounds.

A user usability test of the application involving 40 participants demonstrated the following average success rates: under fundamental functions, the “complete with ease” rate was 98.1% and the “complete with difficulty” rate was 1.9%. Under the advanced functions, the “complete with ease” rate was 82.5%, the “complete with difficulty” rate was 7.5%, and the “failed to complete” rate was 10% (Figure 9). These results indicate that the application has a “very high” success rate, higher than 78%. The other categories, “complete with difficulty” and “failed to complete,” had less than 10%, indicating that it was usual for users to make mistakes when completing the task [41].

Figure 10 presents the satisfaction level with the app and feedback for future development. Overall, 92.5% (n = 40) of the testers were satisfied with the fundamental function of the app and found it effective in alleviating homesickness. For the advanced features, 82.5% (n = 33) of the testers expressed their satisfaction with the app.

5. Discussion

5.1. Influence of Variables on Sounds

This study investigates the influence of demographic diversity and regional variability on sound preferences in China and how Chinese people select sounds that alleviate homesickness. We discovered that various factors affect sounds. For instance, a 57-year-old man from a generic city and a 22-year-old student from the same city would have different sound preferences for coping with homesickness. This implies that altering any of these factors would result in a different sound choice. At the same time, we also observed that people tend to react more strongly to sounds that are distinctive of their hometowns, regardless of the changes in other factors. For example, people from coastal cities were more likely to be moved by the sounds of the sea, while those from urban areas were more likely to be moved by the sounds of city streets. Nature soundscapes from hometowns could create an emotional connection between individuals and their homes, evoking a sense of belonging and potentially offering more effective treatment for homesickness. Additionally, compared with music, nature soundscapes more easily promote relaxation, reduce stress, and enhance focus by immersing listeners in the auditory environment. Therefore, natural sounds could be prioritized in the treatment of homesickness.

5.2. The Contribution of Interaction Design to Sound Therapy

This paper proposes a sound therapy interaction design model based on the psychiatric treatment framework that can contribute to alleviating homesickness from a design perspective. The practical application of this model is demonstrated through the HomeSeek app, which offers personalized homesickness therapeutic experiences. Interaction design is different from other fields in that it focuses on user experience and aims to provide more friendly and convenient solutions to people’s emotional problems. The HomeSeek application provides a new way for people to access therapy. It allows people to access therapy anytime and anywhere, making it easier and faster. A user-use test was conducted on the app, and 92.5% (n = 40) of the testers were satisfied with the app, which shows that the HomeSeek app can help alleviate the problem of homesickness. The result also provides strong support for the validity of the proposed sound therapy interaction model. Moreover, homesickness is sometimes a private emotion, and people sometimes need to self-regulate and adapt. Therefore, interaction design can fulfill the needs of this group of people to heal themselves by interacting with sound by themselves. In terms of the design of the app, compared with traditional apps that rely on visual image effects, the HomeSeek app focuses on the experience that sound brings to people, so it uses a simple and minimalist visual design that helps users focus on sound therapy. Meanwhile, color psychology was considered in the choice of app colors, and blue–green was chosen to give people a calming feeling.

5.3. Inspiration for the Future Development of Inclusive Design

Inclusive design aims to embrace human diversity and difference in terms of ability, language, culture, gender, age, etc. Homesickness is also a manifestation of diversity, and homesick groups should be the target of inclusive design to provide solutions for them. Based on the factors of gender, age, residence status, and reasons for leaving home, this paper also focuses on the geographical differences in Chinese people and introduces new content and insights for inclusive design. The value of the geographically differentiated design in this paper is that it highlights another dimension of content that needs attention in future research on homesickness therapy in different countries. Moreover, this study also considers people’s different needs for sound. Through the HomeSeek app, people can choose a personalized sound therapy program based on their preferences. In subsequent iterations of the application, artificial intelligence algorithms will be used to analyze data such as the frequency and duration of users’ sound choices. This will provide users with more precise sound therapy programs, enhancing the adaptability and universality of the design. This approach meets the needs and expectations of diverse populations in China, thereby increasing the social benefits of homesickness therapy. The sound therapy interaction model proposed in this study can be referenced and adjusted to design products that cater to the unique needs of homesick individuals in different countries and regions, thus helping foreigners cope with homesickness by providing inclusive solutions tailored to diverse characteristics.

There are also differences in individual conditions among those experiencing homesickness. It is noteworthy that the participants recruited for this research were without hearing impairments. However, hearing loss is now a widespread issue. According to the World Health Organization, over 5% of the global population (approximately 430 million people), including 34 million children, suffer from hearing loss. Among the elderly, the prevalence is even higher, with nearly one-fourth of individuals over 60 experiencing disabling hearing loss [42]. Therefore, it is necessary to consider the characteristics of this population when designing homesickness treatments. In future iterations of the HomeSeek app, simple hearing tests, such as tone recognition or speech-in-noise tests, will be implemented. Based on the test results, users will be screened, and the app will adjust the volume of the provided sounds according to the user’s hearing ability. For those with severe hearing loss, alternative suggestions will be offered, making the application more inclusive.

6. Conclusions

This study aims to help Chinese people cope with homesickness, but more importantly, homesickness is a problem that affects people around the world. The sound therapy interaction model proposed in this study takes into account inclusive design and can be adapted and applied in other regions to help foreigners deal with homesickness.

This paper explores the field of interaction design, seeking new methods to alleviate homesickness. This research proposes a sound therapy interaction model and designs a HomeSeek application to demonstrate its practical application. The HomeSeek app allows individuals to self-heal anytime and anywhere, providing a comfortable therapeutic experience. Long-term use of this software may prevent psychological disorders caused by chronic homesickness. It is important to stress that more research on the use of this app in real clinical settings is needed to verify its effectiveness in reducing homesickness. It is also hoped that the findings of this study will serve as a reference for other countries in the future.

This study has some limitations in terms of qualitative research. For future studies, more qualitative research methods will be used, such as focus interviews and participatory observation, to explore and understand users’ needs, emotions, experiences, and behaviors in-depth and to collect personalized data. Moreover, we did not test the effect of combining VR glasses with sound on the users’ sound therapy experiences in the app, which could be another direction for further investigation. Despite these limitations, we believe our work contributes to the current state of the field and hopefully inspires future research.