Mobile health in communication disorders: willingness to use, attitude, advantages, and challenges from the perspective of patients

Abstract

Introduction

Communication disorders are one of the most common disorders that, if not treated in childhood, can cause many social, educational, and psychological problems in adulthood. One of the technologies that can be helpful in these disorders is mobile health (m-Health) technology. This study aims to examine the attitude and willingness to use this technology and compare the advantages and challenges of this technology and face-to-face treatment from the perspective of patients.

Methods

This descriptive study was conducted with a researcher-made questionnaire and investigated the willingness and attitude of patients with communication disorders to use mobile health technology. The face and content validity of the questionnaire were examined with the help of experts in speech therapy, health information management, and medical informatics. Chi-square, Fisher's exact test, and the Kruskal–Wallis test were used to analyze the relationship between variables. Also, the challenges and advantages of mobile health technology and face-to-face treatment were extracted from the patient's answers and presented in the form of main themes and sub-themes.

Results

One hundred seventy patients participated in this study. The results of this study showed that 57 (33.5%) participants preferred face-to-face visits, 11 (6.5%) preferred m-Health, and 102 (60.0%) preferred the combination of mobile applications and the face-to-face visits method. The results showed a statistically significant relationship between "Residence (rural or urban)", "Having trouble traveling to speech therapy centers", and "Delaying treatment due to lack of access to speech therapists" with treatment methods (face-to-face, mobile health, face to face and mobile health). Accessibility and convenience, treatment efficacy and variety, patient empowerment and confidence, family involvement and support, cost and time efficiency, treatment adherence and completion, and comfort and lifestyle compatibility were six categories related to the advantages of mobile health technology from the point of view of patients with communication disorders. Also, technological challenges, effectiveness and quality concerns, patient experience and engagement, and trust and confidence issues were mobile health challenges from the patients' point of view.

Conclusion

The results of this study showed that patients tend to use both face-to-face interactions and mobile health. Integrating both m-Health and traditional methods can optimize speech therapy outcomes. Addressing challenges such as inadequate technological infrastructure and data security is crucial for successful implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-025-12220-y.

Introduction

Communication, a fundamental aspect of human existence, is integral to all human activities. It involves the transmission and reception of thoughts, information, emotions, and ideas, through both verbal and non-verbal means [1]. Given the significance of communication in human life, it is evident that any disorder of this vital ability can have detrimental effects [2]. Communication disorders encompass a broad spectrum of neurodevelopmental and acquired conditions that impair an individual's ability to understand, produce, or use language to interact effectively with others. These disorders can occur at any age and impact various aspects of a person's life, including social interactions, academic and occupational performance, and mental health [3, 4].

Communication disorders affect a substantial portion of the global population, with prevalence estimates ranging from 5 to 10%. In the United States, the prevalence is particularly high among children aged 3 to 17, where 7.7% are diagnosed with disorders involving voice, speech, language, or swallowing [5, 6]. The prevalence of communication disorders varies significantly among children aged 3 to 17. Within this age group, approximately 34% of children between 3 and 10 years old and 25% of those between 11 and 17 years old have some form of communication disorder. Younger children, particularly those aged 3 to 6, exhibit the prevalence at 11%. This rate decreases in older age groups to 9.3% for children aged 7 to 10 and 4.9% for those aged 11 to 17. Additionally, boys are more likely to be diagnosed with communication disorders than girls, with prevalence rates of 9.6% and 5.7%, respectively [7]. Communication disorders impose a substantial economic burden on the United States. These disorders account for an estimated 2.5 to 3% of the nation's Gross Domestic Product (GDP) annually, which translates to between 154 and 186 billion dollars [5].

Research on overcoming communication disorders highlights various methods and approaches. Addressing these challenges requires an integrative and multidimensional strategy. This involves a broad spectrum of interventions such as speech therapy, cognitive approaches, behavioral techniques, technology-assisted methods, and early intervention techniques. Customizing these interventions to cater to the unique requirements of each individual can greatly enhance their communication capabilities [8, 9]. Various technologies are being used in the healthcare field today, including telemedicine, virtual reality, augmented reality, game, and mobile health [10–14]. Technology-assisted methods, such as mobile health apps, are increasingly being leveraged to assist individuals with communication disorders. These innovative applications enhance accessibility to therapy services and enable consistent practice beyond traditional clinical settings [15].

Mobile health apps have emerged as a promising tool for supporting speech-language therapy in adults with communication disorders and children with developmental disabilities. A review of apps targeting adults with communication disorders indicated a varied level of quality, with functional capabilities generally adequate but user engagement relatively low [16]. In parallel, innovative mobile health applications are being developed to address specific communication challenges. For instance, a non-verbal communication app utilizing Google images and animations was designed to facilitate communication for individuals with aphasia [17]. Another study employed a user-centered design approach to create a motor speech disorder therapy app, which was well-received by speech-language pathologists and significantly reduced their workload [18]. In rural South Africa, a self-guided app for caregivers of children with developmental disorders, used as a complement to traditional interventions, demonstrated promising results. Most participants reported regular app use and observed improvements in their children's communication skills [19]. These studies collectively underscore the potential of mobile health apps to address communication disorders across diverse populations and contexts.

Mobile health applications possess considerable potential to enhance the treatment of communication disorders; however, they also encounter substantial challenges [20]. These apps can effectively complement speech therapy and augmentative and alternative communication (AAC). Despite this, issues concerning their quality, efficacy, and accessibility remain prevalent [16, 21]. Critical challenges include ensuring user privacy, securing informed consent, and managing complex data [22]. Additionally, finding high-quality, evidence-based apps is challenging due to app store search algorithm limitations and poor organization [21]. Furthermore, many current apps lack the interactive features and visual appeal required to maintain user engagement in self-directed therapy [16].

To fully leverage the benefits of mobile health technologies, it is crucial to adopt innovative service delivery models, enhance accessibility, and focus on user-centered design. Therefore, addressing these challenges and ensuring the successful implementation of mobile health solutions for communication disorders is essential [23]. Additionally, To prevent the failure of m-Health technology initiatives, it is crucial to evaluate the acceptance level and readiness to utilize this technology at the onset of development [24]. Hence, the objective of this research is to explore the desire of patients suffering from communication disorders (caused by speech, language, and swallowing disorders) before the development of these technologies in this domain.

Method

Study design

This descriptive cross-sectional study aimed to investigate the attitudes and willingness of patients with communication disorders (speech, language, and swallowing disorders) towards the use of mobile health applications.

Participants

The study population comprised individuals diagnosed with communication disorders who were currently receiving speech therapy services at Hamadan University of Medical Sciences. Inclusion and exclusion criteria were applied to select eligible participants.

Inclusion criteria:

• Primary Diagnosis: Individuals diagnosed with a communication disorder (speech, language, or swallowing disorder) by a speech-language pathologist (SLP) or other qualified healthcare professional.

• Diagnostic Assessment: Individuals who have undergone a comprehensive diagnostic assessment, including standardized tests (e.g., standardized language assessments, speech articulation tests, swallowing assessments) and clinical observations.

• Therapy Attendance: Individuals currently attending speech therapy at Hamadan University of Medical Sciences.

Exclusion criteria:

• Inability to Provide Informed Consent: Individuals who are unable to provide informed consent due to cognitive impairment or other reasons.

• Severe Cognitive Impairment: Individuals with severe cognitive impairment that prevents them from understanding and participating in the study.

Sample size

A sample size of 132 participants was calculated using Cochran's formula, considering a margin of error of 0.05 and an estimated population size of 200 patients attending speech therapy clinics at Hamadan University of Medical Sciences during the study period.

Data collection instrument

The instrument used for data collection in this study was a questionnaire developed by the researchers. This questionnaire consisted of four sections: 1) demographic questions, 2) questions assessing attitudes towards and willingness to use m-Health (20 questions), 3) open-ended questions regarding the challenges and benefits of in-person visits and the use of m-Health technology (four questions), and 4) preferred method of treatment (in-person visits, use of m-Health, or a combination of both). Four open-ended questions are presented below:

• 1- What are the perceived advantages of traditional, in-person treatment for individuals with communication disorders?

• 2- What challenges do individuals with communication disorders encounter when participating in traditional therapy settings?

• 3- What are the potential advantages of utilizing mobile health applications in the treatment of communication disorders?

• 4- What are the potential challenges of mobile health applications in speech-language therapy?

It was initially crafted through a review of pertinent scientific literature [25–27] and subsequently refined with the collaboration of experts in speech therapy, health information management, and medical informatics. The validity of the aforementioned questionnaire was assessed through face and content validity. Face validity was evaluated qualitatively by a specialized panel consisting of five individuals, including two speech therapy specialists, two health information management specialists, and one medical informatics specialist. Their feedbacks were incorporated into the questionnaire. Content validity was assessed using both qualitative and quantitative approaches. In the qualitative assessment of content validity, experts in speech therapy, health information management, and medical informatics were requested to provide written feedback after a thorough examination of the instrument. It was underscored that their qualitative evaluation should consider factors such as grammatical correctness, appropriate word usage, the relevance of the questions, the logical sequencing of the questions, and the time required to complete the questionnaire.

Quantitative assessment of content validity was conducted with the collaboration of eight specialists in speech therapy, health information management, and medical informatics, utilizing the Content Validity Ratio (CVR) and Content Validity Index (CVI). The CVR was used to ensure the selection of the most crucial and accurate content, while the CVI was employed to guarantee that the questionnaire’s questions were optimally designed to measure the content. Experts were requested to provide their perspectives on each question in the questionnaire to calculate CVR and CVI. The CVR was calculated using a three-point scale: ‘necessary’, ‘useful but not necessary’, and ‘not necessary’. The CVI was calculated using a four-point scale: ‘1: an irrelevant item’, ‘2: relevant but needs serious revision’, ‘3: relevant but needs minor revision’, and ‘4: extremely relevant item’. Equations (1) and (2) respectively delineate the mathematical relationships that govern the CVR and the CVI.

$$\text{CVR}=\frac{{\text{N}}_{\text{e}}-(\frac{\text{N}}{2})}{\frac{\text{N}}{2}}$$ 1

$$\text{CVI}=\frac{{\text{N}}_{\text{r}}}{\text{N}}$$ 2

In the aforementioned equations, ‘N’ represents the total count of experts, ‘N_e’ denotes the number of experts who categorize an item as "necessary", and ‘N_r’ signifies the count of experts who classify an item as either "relevant but needs minor revision" or "extremely relevant item".

Upon obtaining the experts' responses, we calculated the CVR value for each questionnaire item. These values were then benchmarked against the Lawshe table. Items with a CVR value exceeding 75% were retained in the questionnaire [28]. At this stage, two questionnaire items were eliminated due to their computed CVR values did not meet the 75% threshold. In addition, we computed the CVI value for each questionnaire item using its respective formula and compared it with the Waltz and Basel content validity index. Items with a CVI value exceeding 79% were included in the questionnaire [29, 30]. After the validity assessment, the questionnaire’s reliability was quantified via Cronbach’s alpha, yielding a value of 0.845.

Data analysis

The collected data was analyzed using descriptive statistics (e.g., frequency, percentage, mean, standard deviation) and inferential statistical tests. Additionally, this study examined the relationship between the "preferred treatment method (in-person visit, use of mobile health technology, or a combination)" and the following variables: "place of residence (urban or rural)", "the number of therapy sessions per month", "distance from residence to therapy center", "ability to pay treatment costs", "types of disorders", "having personal transportation to go to the speech therapy center", "having trouble traveling to speech therapy centers", "delaying treatment due to lack of access to speech therapists", "ceasing treatment prematurely due to fatigue, a lack of patience, and insufficient time", and "experience of using mobile health". To examine the relationships between these variables, Chi-square, Kruskal–Wallis, and Fisher's exact tests were employed. Thematic analysis was employed to analyze qualitative data related to participants' perceptions of mobile health applications. To conduct thematic analysis, the patients' answers were imported into the ATLAS.ti software. The responses were reviewed several times, and codes, sub-themes, and main themes were extracted.

Ethical considerations

The study was conducted in accordance with ethical principles, and informed consent was obtained from all participants. We declare that we used an artificial intelligence-based tool (gemini) to translate this article.

Results

Demographic information of responders

Two hundred fifty patients who met our inclusion and exclusion criteria referred to medical centers for communication disorders were given questionnaires, and 170 were answered (response rate: 68%). Although the sample size was calculated to be 132 patients, the authors provided the questionnaire to all the people who visited the medical centers during the study. Out of 170 questionnaires, 35 were answered by people with communication disorders, and 135 were answered by the parents of the patients due to the children's young age. 106 of 135 parents and 18 of 35 patients were women. Among the respondents, 144 (84.7%) lived in urban areas, and 26 (15.3%) lived in rural areas.

Results of patient survey on m-Health

The frequency (percentage) of responses and mean score out of 5 are given in Table 1. Among the answers, the highest mean scores obtained were related to the questions "In treatment via mobile phone, compared to face-to-face visits, I will have to travel less distance and also spend less money" and "I will only use these applications if my therapist provides them to me and advises me to use them" with a mean score of 4.1 and 4. The lowest score was related to the question, "These applications can replace face-to-face therapy," with a mean score of 1.95.

Table 1.

Frequency (percentage) and mean score of people's attitude towards mobile health in speech therapy

#	Questions	Strongly agree N (%)	Agree N (%)	Neutral N (%)	Disagree N (%)	Strongly disagree N (%)	Mean Score out of 5
1	In treatment via mobile phone, I can devote more time to the treatment compared to face-to-face visits	44 (25.9)	40 (23.5)	31 (18.2)	43 (25.3)	12 (7.1)	3.36
2	Compared to face-to-face visits, I will be treated sooner in treatment via mobile phone	23 (13.5)	23 (13.5)	44 (25.9)	58 (34.1)	22 (12.9)	2.80
3	Compared to face-to-face visits, my treatment costs will be lower in treatment via mobile phone	61 (35.9)	59 (34.7)	31 (18.2)	16 (9.4)	3 (1.8)	3.93
4	In treatment via mobile phone, I will have higher self-confidence compared to a face-to-face visits	28 (16.5)	29 (17.1)	52 (30.6)	44 (25.9)	17 (10.0)	3.04
5	In treatment via mobile phone, I will have less anxiety and stress compared to a face-to-face visits	36 (21.2)	48 (28.2)	25 (14.7)	49 (28.8)	12 (7.1)	3.28
6	Compared to face-to-face visits, the treatment program will progress better in treatment via mobile phone	16 (9.4)	29 (17.1)	42 (24.7)	66 (38.8)	17 (10.0)	2.77
7	Compared to a face-to-face visits, my adherence to treatment plans will be higher in treatment via mobile phone	28 (16.5)	30 (17.6)	30 (17.6)	63 (37.1)	19 (11.2)	2.91
8	Compared to face-to-face visits, I will receive better and higher quality speech therapy services in treatment via mobile phone	17 (10.0)	19 (11.2)	46 (27.1)	65 (38.2)	23 (13.5)	2.66
9	Compared to face-to-face visits, I can better adapt my lifestyle to the therapy plan in treatment via mobile phone	39 (22.9)	35 (20.6)	45 (26.5)	44 (25.9)	7 (4.1)	3.32
10	Compared to face-to-face visits, I can follow treatment instructions better and more efficiently in treatment via mobile phone	32 (18.8)	45 (26.5)	28 (16.5)	53 (31.2)	12 (7.1)	3.2
11	Compared to face-to-face visits, I will have fewer challenges in treatment via mobile phone	32 (18.8)	51 (30.0)	23 (13.5)	49 (28.8)	15 (8.8)	3.21
12	In treatment via mobile phone, compared to face-to-face visits, I will have to travel less distance and also spend less money	71 (41.8)	67 (39.4)	15 (8.8)	12 (7.1)	5 (2.9)	4.1
13	In treatment via mobile phone, I only need a few technical skills, and I do not need to dedicate much time to learning them	13 (7.6)	57 (33.5)	26 (15.3)	50 (29.4)	24 (14.1)	2.91
14	Treatment via mobile phone will be more attractive and fun than face-to-face visits	29 (17.1)	36 (21.2)	38 (22.4)	52 (30.6)	15 (8.8)	3.07
15	Using mobile applications does not negatively affect the therapist's behavior or change the relationship between the therapist and me	10 (5.9)	52 (30.6)	69 (40.6)	25 (14.7)	14 (8.2)	3.11
16	In treatment via mobile phone, compared to face-to-face visits, the progress in the treatment is determined, and the therapist is not needed to determine the progress	3 (1.8)	13 (7.6)	37 (21.8)	68 (40.0)	49 (28.8)	2.13
17	I will only use these applications if my therapist provides them to me and advises me to use them	61 (35.9)	73 (42.9)	18 (10.6)	12 (7.1)	6 (3.5)	4.00
18	These applications can replace face-to-face therapy	5 (2.9)	9 (5.3)	24 (14.1)	67 (39.4)	65 (38.2)	1.95
19	I am willing to pay to use these applications, and I will use them if they are free or not	8 (4.7)	48 (28.2)	36 (21.2)	36 (21.2)	42 (24.7)	2.67
20	In face-to-face visits, the treatment process may remain incomplete, but with the help of these technologies, it will be completed	29 (17.1)	52 (30.6)	28 (16.5)	45 (26.5)	16 (9.4)	3.19

The results of this study showed that 57 (33.5%) participants preferred face-to-face visits, 11 (6.5%) preferred m-Health, and 102 (60.0%) preferred the combination of mobile applications and the face-to-face visits method. The results of the chi-square test (Table 2) showed that there was no statistically significant relationship (p-value = 0.977) between the two groups of responders (patient or parent) and treatment method (face-to-face, mobile applications, both of them).

Table 2.

Examining the relationship between the type of treatment (face-to-face, mobile applications, both of them) in the group of respondents

	Face-to-face visits	Mobile application	Face-to-face visits & Mobile application	Total	P-value
	Frequency (percent)	Frequency (percent)	Frequency (percent)	Frequency (percent)
Patient	12 (34.3)	2 (5.7)	21 (60.0)	35 (20.6)	0.977
Parents	45 (33.3)	9 (6.7)	81 (60.0)	135 (79.4)
Total	57 (33.5)	11 (6.5)	102 (60.0)	170 (100)

Among the 170 participants in this study, 26 (15.3%) were rural area residents, and 144 (84.7%) were urban area residents. In both rural and urban populations, patients expressed a preference for a combination of in-person and mobile health services. The chi-square test results showed a statistically significant relationship between residence (rural or urban) and treatment method (P-value = 0.001) (Table 3).

Table 3.

Relationship between residence (rural or urban) and treatment method

	Face-to-face visits	Mobile application	Face-to-face visits & Mobile application	Total	P-value
	Frequency (percent)	Frequency (percent)	Frequency (percent)	Frequency (percent)
Rural area residents	7 (12.3)	6 (54.5)	13 (12.7)	26 (15.3)	0.001
Urban area residents	50 (87.7)	5 (45.5)	89 (87.3)	144 (84.7)
Total	57 (33.5)	11 (6.5)	102 (60.0)	170 (100.0)

According to the results reported in Table 4, the mean of speech therapy sessions for the participants in this study was five sessions during one month. Examining the variable "Distance to speech therapy clinics" also showed that the mean distance to the speech therapy center for the group who preferred to use mobile applications for treatment was 28 km, which was more than the other two groups. However, the results of the Kruskal–Wallis test showed that the mean of "number of speech therapy sessions during a month" (p-value = 0.201) and "Distance to speech therapy clinics" (p-value = 0.393) in different categories of "treatment method" variable did not differ from each other.

Table 4.

Relationship between number of sessions and distance and treatment method

Variable	Face-to-face visits	Mobile application	Face-to-face visits & Mobile application	Total	P-value
	Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)
Number of speech therapy sessions during a month	4.19 (1.49)	7.27 (6.41)	4.68 (2.30)	4.68 (2.62)	0.201*
Distance to speech therapy clinics	13.94 (21.18)	28.03 (31.94)	18.75 (29.29)	17.74 (27.09)	0.393*

^*Kruskal–Wallis Test

Among the respondents, 70.6% of patients reported being able to afford healthcare costs. 51.2% of patients did not have access to personal transportation for medical appointments, and 41.2% reported difficulties in commuting to healthcare facilities. 40.6% of patients stated that they had delayed their treatment due to a lack of access to healthcare providers. 15.9% of patients reported prematurely discontinuing treatment due to fatigue, a lack of patience, and insufficient time (Table 5). The relationship between different variables with the tendency to use different treatment methods (face-to-face, mobile applications, both of them) was investigated. According to the results reported in Table 5, only the relationship between the variables "Having trouble traveling to speech therapy centers" (P-value = 0.007) and "Delaying treatment due to lack of access to speech therapists" (P-value = 0.007) with "treatment method" was statistically significant.

Table 5.

Relationship between different variables and treatment method

	Subcategory	Face-to-face visits	Mobile application	Face-to-face visits & Mobile application	Total	P-value
		Frequency (percent)	Frequency (percent)	Frequency (percent)	Frequency (percent)
Ability to pay treatment costs	Yes	45 (78.9)	6 (54.5)	69 (67.6)	120 (70.6)	0.157**
	No	12 (21.1)	5 (45.5)	33 (32.4)	50 (29.4)
Types of disorders	Language	8 (14.0)	2 (18.2)	23 (22.5)	33 (19.4)	0.779*
	Speech	40 (70.0)	7 (63.6)	58 (56.9)	105 (61.8)
	Swallow	1 (1.8)	-	6 (5.9)	7 (4.1)
	Speech & swallow	2 (3.5)	-	5 (4.9)	7 (4.1)
	Speech & language	5 (8.8)	2 (18.2)	9 (8.8)	16 (9.4)
	Speech, language & swallow	1 (1.8)	-	1 (1.0)	2 (1.2)
Having personal transportation to go to the speech therapy center	Yes	27 (47.4)	5 (45.5)	51 (50.0)	83 (48.8)	0.926**
	No	30 (52.6)	6 (54.5)	51 (50.0)	87 (51.2)
Having trouble traveling to speech therapy centers	Yes	14 (24.6)	6 (54.5)	50 (49.0)	70 (41.2)	0.007**
	No	43 (75.4)	5 (45.5)	52 (51.0)	100 (58.8)
Delaying treatment due to lack of access to speech therapists	Yes	14 (24.6)	4 (36.4)	51 (50.0)	69 (40.6)	0.007**
	No	43 (75.4)	7 (63.6)	51 (50.0)	101 (59.4)
Ceasing treatment prematurely due to fatigue, a lack of patience, and insufficient time	Yes	6 (10.5)	1 (9.1)	20 (19.6)	27 (15.9)	0.264**
	No	51 (89.5)	10 (90.9)	82 (80.4)	143 (84.1)
Experience of using Mobile Health	Yes	7 (12.3)	-	6 (5.9)	13 (7.6)	0.207*
	No	50 (87.7)	11 (100.0)	96 (94.1)	157 (92.4)
Total		57 (33.5)	11 (6.5)	102 (60.0)	170 (100.0)

^*Fisher's Exact Test

^**Chi-Square Test

Results of thematical analysis

As described in the methodology section, the questionnaire included four open-ended questions regarding the advantages and disadvantages of both in-person visits and the use of mobile health. Patients' responses were analyzed using ATLAS.ti, and four thematic maps were extracted. Examples of patients' responses are presented below:

"In-person visits allow therapists to more accurately assess patients' progress in their office."

"For my family and I, who live far from a healthcare center, using mobile health services is more convenient and cost-effective."

"I think in-person speech therapy sessions where the speech-language pathologist can observe my performance and provide immediate feedback are very beneficial."

"With mobile health, treatment can be conducted at home."

"In in-person treatment, the physician can directly verify the patient's progress."

"I might not be able to complete my in-person treatment."

Thematic map of the advantages of face-to-face therapy is displayed in Fig. 1. The advantages mentioned in three main themes include: 1. Therapist-patient interaction, 2. Treatment effectiveness and quality and 3. Patient experience and comfort.

Fig. 1.

Thematic map of advantages of face-to-face therapy

Patients believed that in-person therapy sessions had many benefits. These benefits included the ability for the therapist to directly observe and provide rapid feedback to patients, as well as improved learning and skill acquisition by patients. In addition, respondents believed that in-person visits could lead to faster progress and reduced treatment time.

In addition, study participants believed that in-person therapy created a more conducive therapeutic environment and enabled the patient to actively participate in the treatment process. They believed that in-person visits made it easier to plan and coordinate treatment interventions, leading to better communication and trust between the therapist and the patient. They also provided opportunities for ongoing counseling and support. Patients also believed that because in-person therapy allows therapists to directly observe the patient, they could better manage the patient’s treatment process.

Figure 2 shows the challenges of face-to-face treatment from the perspective of patients. The mentioned challenges were classified into three main themes: accessibility and convenience, economic factors, and patient engagement and compliance.

Fig. 2.

Thematic map of challenges of face-to-face therapy

Regarding the challenges associated with in-person therapy, study participants believed that some children feel embarrassed during therapy sessions, and this may affect the treatment process. In addition, they believed that families may abandon therapy for a variety of reasons.

In addition, participants believed that the costs of in-person therapy sessions may limit their access to therapy, which may disrupt treatment. Participants believed that other challenges, such as long distances or transportation problems, could prevent patients from attending therapy sessions regularly. In their opinion, these challenges included restrictions on public transportation or lack of adequate parking facilities at treatment centers. Also, the time that patients or their families have to spend attending treatment centers was another challenge for them.

Figure 3 shows the advantages of mobile health. Accessibility and convenience, treatment efficacy and variety, patient empowerment and confidence, family involvement and support, cost and time efficiency, treatment adherence and completion, and comfort and lifestyle compatibility were six categories related to the advantages of this technology from the point of view of patients with speech disorders.

Fig. 3.

Thematic map of advantages of mobile health

"Regarding the benefits of m-Health, participants stated that this technology can enable patients to access healthcare services from their homes, thus eliminating the need to visit a therapist in person and travel long distances to receive treatment. They believed that mHealth provides 24-h access to healthcare, reduces waiting times, and provides timely care, especially in remote or underserved areas where healthcare facilities are not available. In addition, patients can track their treatment process at any time of the day or night without having to visit a healthcare facility.

Patients stated that m-Health has the potential to reduce healthcare costs, minimize absenteeism for patients and parents, and lead to better time management, as it allows individuals to access care during breaks or other convenient times. Parents of children believed that engaging features in m-Health applications could lead to greater adherence to treatment plans for children. "Mobile health can create opportunities for individuals to practice skills and techniques at home, enhance learning, and eliminate the need for frequent travel to receive medical care."

Mobile health challenges from the point of view of patients were categorized into four classifications (Fig. 4): 1. Technological challenges, 2. Effectiveness and quality concerns, 3. Patient experience and engagement, and 4. Trust and confidence issues.

Fig. 4.

Thematic map of challenges of mobile health

Participants believed that the use of m-Health can also have many challenges. One key issue is the potential for increased distraction in children while using mobile devices. In m-Health, there may be a lack of immediate feedback from therapists, which is important. Excessive use of mobile devices can lead to social isolation and loneliness, especially in children. In addition, prolonged use of mobile devices may lead to eye problems.

Patients believed that people may not be technologically literate enough to use mobile apps. Some patients also had doubts about the effectiveness of m-Health. Patients believed that technical difficulties, such as poor internet connectivity, can be a barrier to using the technology.

Monitoring and evaluating patient progress in m-Health interventions is challenging. M-Health may not be as effective as traditional in-person therapy. In addition, therapists may have difficulty effectively monitoring patient progress in m-Health interventions.

Discussion

This study investigated patients' willingness to use mobile health applications for communication disorders. Key findings include their desire to adopt these technologies, preferences for treatment modalities (face-to-face, mobile application, or both), and the influence of geographic location and therapy session frequency on treatment choices. The discussion will delve deeper into these findings, exploring the perceived benefits and challenges of both face-to-face and mobile health interventions.

In this study, a total of 170 questionnaires were completed, representing a 68% response rate. This high participation rate indicates a strong willingness among patients to actively engage in the research. Notably, among the respondents, 106 of 135 parents and 18 of 35 patients were female. This gender distribution suggests a higher participation rate among women. Similarly, a study conducted in Iran revealed that 66.9% of speech-language pathologists participating in a survey were female [25]. This finding indicates that gender may influence individuals’ participation in communication disorder research. Furthermore, a review of studies utilizing mobile health applications for diabetes management [31], smoking cessation [32], and coronary heart disease [33] has shown higher rates of participation and usage among women compared to men. Several factors may contribute to this trend. Research indicates that women tend to seek medical services more frequently than men, a pattern that could extend to research participation. Additionally, women often assume caregiving roles, leading to greater involvement in their children’s health-related activities [34–36]. Sociocultural norms may also encourage women to be proactive about health issues, fostering their willingness to engage in research studies [37]. In this study, due to children’s inability to answer the questionnaire directly, parents provided responses on their behalf. A review of studies in the field of remote medical and therapeutic services for children reveals an emerging trend: parents are increasingly assuming the role of co-therapists. In this context, parents receive instructions and stimuli, actively supporting their child by assessing speech accuracy and overall condition. This collaborative approach contributes to enhancing and expediting the treatment process [38, 39].

The findings of this study indicate that the majority of participants (60.0%) preferred a combination of mobile applications and face-to-face visits, suggesting that a hybrid approach to healthcare delivery may be more acceptable to patients compared to exclusively face-to-face visits (33.5%) or m-Health alone (6.5%). This highlights the potential for integrating digital health solutions with traditional care models to better meet patient preferences. This preference aligns with broader research trends, which suggest that while mobile health applications offer significant benefits for individuals with communication disorders, a hybrid approach combining mobile applications with in-person visits is often preferred. Patients appreciate the convenience and cost-effectiveness of mobile health services but still value the personalized attention and comprehensive assessments provided through in-person visits [40]. Patient feedback from studies conducted during the COVID-19 pandemic indicated a preference for telehealth speech therapy. However, a flexible approach that incorporates both telehealth and in-person visits was seen as essential for ensuring continuity of care and addressing the unique needs of individual patients [41, 42]. Overall, integrating both approaches can enhance speech therapy outcomes. Numerous studies highlight the potential advantages of technology in speech therapy, such as enhanced adherence, convenience, and cost reduction. Nevertheless, face-to-face interactions remain crucial for specific treatment aspects, including faster progress and higher service quality [38, 43].

The study findings indicated a statistically significant correlation between place of residence (rural or urban) and the preferred treatment method (face-to-face, mobile applications, or both). Among the variables affecting treatment method selection, 'Having trouble traveling to speech therapy centers' and 'Delaying treatment due to lack of access to speech therapists' were the only factors showing a statistically significant association with the chosen treatment method. These findings align with the results of a study by Greenberg et al., which revealed that, despite similar rates of smartphone ownership and health app installations, rural residents were less likely to engage with digital health tools for communicating with healthcare providers or managing personal health information online. This suggests that rural residents, while having access to technology, may face barriers in effectively utilizing digital health tools for healthcare purposes [44]. Research indicates that there are substantial disparities between rural and urban regions concerning socio-economic conditions, access to healthcare, and lifestyle variations. These differences notably affect individual preferences for treatment modalities. Additionally, elements such as the cost of healthcare and the duration of waiting periods for medical services are significant factors influencing these preferences [39–41].

The study highlights the significant benefits of face-to-face therapy for patients with communication disorders, categorized into therapist-patient interaction, treatment effectiveness and quality, and patient experience and comfort. Key advantages include effective therapeutic monitoring, enhanced expertise, better patient focus and learning, and a more enjoyable and consistent treatment experience. These findings underline the importance of face-to-face therapy in providing comprehensive and high-quality care. In line with the results of the present study, previous research has consistently demonstrated the advantages of in-person therapy for those with communication disorders. These benefits encompass stronger therapeutic bonds, improved nonverbal cues, greater patient participation, more precise assessment and diagnosis, and better skill transfer [45–47]. Notably, some studies have indicated that online therapy can be effective in specific contexts, such as remote or underserved areas [48, 49]. Variations in study design, population characteristics, and therapeutic modalities may account for the differences in findings. This underscores the need for further research to identify the most effective approaches for different patient groups and settings.

Although face-to-face therapy has its benefits in treating communication disorders, the drawbacks of this treatment method from the patients' perspective in this study were significant, including challenges such as scheduling difficulties, transportation barriers, and financial constraints, thus highlighting the need to explore alternative delivery models like mobile health to improve accessibility. Consistent with the present study's findings, previous research has identified significant limitations associated with face-to-face therapy, particularly regarding accessibility and convenience. Several studies have consistently highlighted challenges such as geographic barriers, transportation issues, and scheduling conflicts as substantial obstacles for individuals seeking in-person therapy. Furthermore, emotional and social factors, including anxiety, discomfort, and social stigma, have been found to potentially impact patient engagement and adherence to treatment [50–52]. In light of these constraints, it would be prudent to consider exploring and implementing alternative service delivery models, such as mobile health, with the aim of enhancing accessibility and improving outcomes for individuals experiencing communication disorders.

As previously noted, a primary objective of this study is to examine the advantages of employing mobile applications in the treatment process for patients with communication disorders. From the patients' perspective, these benefits encompass a range of factors, including increased flexibility and accessibility of treatment services, enhanced treatment efficacy, facilitation of family engagement and support, augmented patient empowerment, and promotion of comfort and adaptation to individual lifestyles. The findings of this study are further corroborated by other research highlighting the substantial benefits of mobile health applications in treating patients with communication disorders. In exploring the advantages of mobile health technology for speech, language, and swallowing disorders, studies have shown that this technology enables remote access to assessment and treatment services, which is particularly advantageous for patients in rural or underserved areas [12, 25]. This approach effectively bridges geographical gaps, ensuring that individuals can receive care regardless of their location. Uninterrupted treatment is achievable, even during travel or emergencies, leading to enhanced treatment outcomes [21]. Additionally, m-health programs consistently demonstrate reductions in waiting times and associated costs, emphasizing the benefit of faster access to care for patients and resource optimization [53]. In the context of speech, language, and swallowing disorders, m-Health tools provide features such as reminders, notifications, and interactive elements to improve treatment adherence [54]. These user-friendly applications can be tailored to individual needs, with speech therapy programs targeting specific speech sounds or language skills [11], and swallowing programs offering exercises tailored to a patient’s unique swallowing issues. Personalized interventions not only boost patient engagement but also lead to improved treatment outcomes [55]. By allowing patients to perform exercises conveniently at home, mobile health apps encourage consistent practice and empower patients to actively participate in their rehabilitation process, reducing the need for frequent clinic visits [56].

While mobile health technology offers significant benefits in the realm of speech, language, and swallowing disorders, specific challenges hinder its overall efficacy. This study reveals various obstacles, such as technological barriers, concerns regarding effectiveness and quality, and patient engagement challenges, all of which can considerably influence the success of mobile health interventions for individuals affected by communication disorders. In line with the results of the present study, previous research has identified several challenges associated with the use of mobile health technology in communication disorders, such as a lack of evidence-based standards, privacy concerns, provider literacy, patient acceptance, and reimbursement issues [25, 57, 58]. Given the challenges identified in this study and others, it is crucial to explore potential solutions to mitigate these obstacles. Building upon the insights gained from previous research and the present findings, the subsequent section will present various strategies to address these issues, with the goal of optimizing mobile health interventions for individuals with communication disorders.

Inadequate technological infrastructure may impede the successful implementation of m-health solutions. Challenges such as poor internet connectivity, outdated devices, or limited smartphone access can arise [59, 60]. In this regard, studies have demonstrated a considerable gap in internet access and digital technology utilization among various patient populations, particularly between urban and rural dwellers [61]. Urban areas generally benefit from stronger communication infrastructure, higher rates of smart device ownership, and increased digital literacy. In contrast, rural residents often face constraints such as limited internet access, slow connection speeds, high costs, and lower digital literacy levels. These disparities have a direct bearing on individuals' ability to seek health information, employ health applications, and engage in digital healthcare services [62, 63]. To address and mitigate technological infrastructure challenges, in addition to government and organizational efforts to improve and develop infrastructure, it is advisable to design mobile health programs with offline functionality. This ensures that users can access essential features even without an internet connection.

Patients vary in their digital literacy and comfort with using digital tools. Some individuals may struggle with mobile app usage, understanding instructions, or resolving technical issues [64]. Consequently, prioritizing patient education and providing adequate support is crucial. In this context, the following recommendations are proposed: customize patient education programs to individual needs, assess each patient’s digital proficiency, and provide targeted training on using mobile apps and understanding instructions. Additionally, design intuitive and user-friendly interfaces for mobile health apps, minimizing complexity and incorporating clear language and visual aids. Consider creating short video tutorials or interactive guides within the app to demonstrate program features, troubleshooting steps, and common tasks.

Reimbursement limitations pose another challenge in the adoption of mobile health technology. Existing reimbursement policies and regulations may not comprehensively cover or incentivize m-health services. Speech-Language Pathologists (SLPs) may encounter difficulties in obtaining compensation for their virtual consultations [25, 64]. To address and mitigate this challenge, consider advocating for customized reimbursement policies specifically covering m-health services. These policies should promote virtual consultations for SLPs and other healthcare providers. Engage with insurance companies and payers to ensure adequate reimbursement for virtual consultations, emphasizing the value and affordability of m-health solutions. Educate policymakers, healthcare managers, and SLPs about the benefits of m-health, raising awareness of the need for equitable reimbursement for virtual care.

Ensuring patient privacy and maintaining data security are critical aspects of mobile health programs. SLPs must proactively address concerns related to data breaches, confidentiality, and secure communication channels [65, 66]. To address the challenge of maintaining data security and protecting patient privacy in mobile health apps, consider the following solutions: implement strong encryption protocols for data transmission and storage, ensuring that sensitive patient information remains confidential and secure. Obtain informed consent from patients regarding data collection, storage, and use, and clearly communicate privacy policies and data handling practices. Conduct periodic security audits to identify vulnerabilities and promptly address any weaknesses to prevent data breaches.

Although this study offers insightful perspectives on the attitudes and willingness of individuals with communication disorders towards mobile health applications, it is crucial to recognize its limitations. Notable strengths of the study encompass a robust methodology, the utilization of a valid and reliable instrument, a comprehensive mixed-methods approach, well-defined participant selection criteria, and adherence to ethical research principles. Nonetheless, the study's generalizability may be constrained by its single-site nature and cross-sectional design. Furthermore, the potential influence of response bias in self-reported data should be acknowledged. Future research endeavors should examine the long-term impact of mobile health applications through longitudinal studies, investigate the generalizability of findings across diverse populations and healthcare settings, and conduct further investigations into factors influencing response patterns.

Conclusion

The results of this study reveal a significant inclination (60.0%) towards a hybrid treatment approach, incorporating mobile health applications in conjunction with traditional face-to-face therapy for individuals with communication disorders. This preference signifies the importance of developing an integrated healthcare delivery model in speech therapy that combines digital solutions with conventional therapeutic methods, rather than supplanting one with the other. By addressing typical barriers such as scheduling conflicts and transportation challenges associated with in-person therapy, and capitalizing on the engaging and adaptable attributes of mHealth applications, this integrated model holds the potential to offer continuous support and monitoring for patients. Furthermore, the present study underscores the impact of demographic factors, including gender and residential location, on the acceptance and efficacy of various treatment modalities. These observations accentuate the necessity for healthcare systems to consider these variables during the design and execution of integrated care models, ensuring tailored and equitable care delivery.

Future investigations should concentrate on establishing evidence-based standards for mobile health applications, devising strategies to bolster privacy and security measures, improving provider and patient literacy, and tackling reimbursement and regulatory challenges. Longitudinal studies are also necessary to evaluate the long-term effects of mobile health applications on patient outcomes and to discern how patient attitudes towards these technologies develop over time. By addressing these areas, we can more effectively harness the potential of mobile health technology to augment and enrich traditional therapeutic methods, thereby enhancing the quality and accessibility of care for patients affected by communication disorders.

Authors' contributions

SS, TKH, HB, MSS developed the concept for the study. SS and TKH carried out the analysis and interpretation under the supervision of MGS. SV, SS and SHA collected data. Finally, SS, TKH, MSS, and HB drafted the manuscript. All authors reviewed the content and approved it.

Funding

This work was supported by a grant from Hamadan University of Medical Sciences Research Council (ID: 140008046281).

Data availability

All data generated or analyzed during this study are included within this article.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki and approved by a local ethics committee in Iran, namely Ethics Committee of the Hamadan University of Medical Sciences (ethics approval number:IR.UMSHA.REC.1400.524). Verbal informed consent obtained from all the participants included in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.