Knowledge Is (Still) Key: Awareness to Shape Trends in Telemedicine Use during the Pandemic Based on Management Perceptions and Implementation Systems

Hawa, Nada I.; Soesilo, Tri E. B.; Nuraeni, Nuraeni

doi:https://doi.org/10.1155/2023/4669985

International Journal of Telemedicine and Applications

On this page

Abstract Introduction Materials and Methods Results Discussion Conclusions Data Availability Ethical Approval Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 4669985 | https://doi.org/10.1155/2023/4669985

Knowledge Is (Still) Key: Awareness to Shape Trends in Telemedicine Use during the Pandemic Based on Management Perceptions and Implementation Systems

Nada I. Hawa,¹Tri E. B. Soesilo,²and Nuraeni Nuraeni³

Academic Editor: Arnauld Nicogossian

Received14 Jun 2023

Revised01 Sept 2023

Accepted24 Nov 2023

Published06 Dec 2023

Abstract

Objectives. The digital revolution has brought rapid developments to the health sector. People were taking advantage of telemedicine technology during the COVID-19 pandemic. Telemedicine is highly recommended during a pandemic because it will reduce the transmission rate of viruses, and it is considered adequate and low-cost. However, a fundamental challenge still occurs; most people need to be used to telemedicine technology. Presumably, inadequate education and lack of experience regarding the use of telemedicine are obstacles for society in utilizing telemedicine. Methods. This study is aimed at determining the factors that influence the use of telemedicine. It focused on variables such as data confidentiality, administration, and knowledge to measure potential factors that pushed people to utilize telemedicine. We used a quantitative approach, using multivariate analysis, namely, simple linear regression. Most of our respondents are people aged 18-30 years young. Results. All respondents stated that administration factors in the implementation of telemedicine were good. Through the Chi-square test, the data safety factor has no effect ( value =0.090 or >0.05) on telemedicine implementation, while the knowledge factor has a significant effect on telemedicine implementation with a value =0.043 (<0.005). The multivariate analysis explained that the knowledge variable influenced telemedicine use with a value =0.033 (<0.05), meaning it contributed 1.624 times to telemedicine. Conclusion. This study discusses the factors that influence the use of telemedicine. The study’s results explain that the knowledge variable is the most significant factor influencing telemedicine use. Knowledge is an intellectual property that everyone must have to capitalize on with telemedicine. A lack of knowledge will become an information gap and a barrier for someone to reach new tools/technologies.

1. Introduction

Advances in technology bring increasingly sophisticated aspects to the health sector. Telemedicine is an evidence-based practice resulting from technological developments [1]. Three pillars shape the telemedicine trend. The first is remote patient monitoring (RPM), which means remote patient control. The second is teleconsultation, namely, consultation between patients and health workers, for example, via web videos. The third is direct monitoring from home [2]. The advantage of telemedicine is that it is easy for patients to consult with doctors [3] and saves time and costs [4–7]. In addition, telemedicine can provide services via web video between service providers or health workers and patients in various remote areas [8]. Therefore, this approach can increase openness about the disease between service providers and patients because the younger generation finds telemedicine consultations more comfortable than consulting directly with health workers [9].

Telemedicine is increasing, especially during the COVID-19 pandemic, and there is great hope for the public to continue to consult with health workers [10]. Contactless consultations can ensure a safe relationship between patients and healthcare workers [11] and help avoid cross-infection [12]. Our research was conducted in Indonesia because Indonesia is known for the rapid spread of the COVID-19 virus among the people [10]. In a way, Indonesia, as a developing country, has specific social dynamics that determine the process of adopting a relatively new technological approach, which in this case refers to telemedicine. Therefore, the application of telemedicine during a pandemic needs to be studied by considering various factors in this field of study. A study by Hawrysz et al. explained that during the COVID-19 pandemic, patient satisfaction with telemedicine increased [13]. In a similar statement, providing online treatment is the best intervention during the COVID-19 pandemic, which can reduce the risk of transmission of COVID-19 [14]. However, testing these assumptions in the context of our research would be interesting. Here is a little more explanation regarding the condition of telemedicine in Indonesia. Currently, Indonesia has 17 telemedicine services, namely, Aido Health, Alodokter, Getwell, Good Doctor, Halodoc, Homecare24, KlikDokter, KlinikGo, Lekasehat, LinkSehat, Mdoc, Milvik Dokter, ProSehat, Sehatq, TrustMedis, Vascular Indonesia, and YesDok [15].

The current debate is centered on the issue of the lack of information and education that hinders people from accessing telemedicine technology. Telemedicine is used to increase digital literacy and technological resources [16]. Increasing digital literacy for the community can be done by providing education/information. Therefore, telemedicine can be applied to a broader field of health. Telemedicine allows health workers to treat children, refer patients to health services, treat patients virtually, or conduct consultations [17]. Based on previous research, the obstacles to using telemedicine are age and educational level [18–20]. The older the age, the longer it takes for individuals to receive new technology, and parents prefer to consult directly with health facilities rather than telemedicine [20].

At the same time, education level is a telemedicine obstacle because research also finds that the lower a person’s education, the lower that person’s knowledge, which is called a digital literacy deficit. Another weakness of telemedicine is that health workers cannot carry out physical examinations in person, so they are limited in providing emergency services. In addition, users need stable connectivity to access telemedicine services [7, 17]. However, there is still work to be done, particularly regarding differences in preferences based on knowledge and practical telemedicine applications. Our study contributes to exploring and predicting variables in sustainable telemedicine adoption.

2. Materials and Methods

2.1. Study Design and Sampling

This study was conducted in Surabaya City, East Java Province, Indonesia. This study uses a quantitative approach with a cross-sectional design. Surabaya, the capital city of East Java, is home to people of various ethnicities. The locals are joined by foreigners who came from other areas and settled in the area, which has resulted in the area being densely populated. Consequently, the spread of the COVID-19 virus is rapidly happening in this city.

Previous research has been conducted on telemedicine using a retrospective observational study method because of doubts arising during diagnosis and therapeutic management [21]. Meanwhile, this study is aimed at determining the factors that influence the use of telemedicine. It is essential to generate a perspective on which factors should be considered important and worthy of attention to implementing telemedicine technology in the healthcare sector, such as user knowledge [16, 22, 23] and perceptions regarding data security [24, 25] and administration in telemedicine practices [26, 27]. The conceptual framework for this research can be seen in Figure 1.

Hypothesis 1. Perception of data security influences the perceptions of telemedicine implementation.

Hypothesis 2. Perception of administration influences the perceptions of telemedicine implementation.

Hypothesis 3. The knowledge factor influences the perception of telemedicine implementation.

2.2. Sample Size Determination and Sampling Procedure

We used a simple random sampling method and selected respondents based on several inclusion criteria: telemedicine service users and smartphone users. We adjusted the inclusion criteria to the research objective, namely, the determining factors for the use of telemedicine, where people generally access telemedicine via smartphones. The number of respondents in this study was 400 respondents. The entire research process was carried out for one year in 2022 after COVID-19 hit.

2.3. Measures

Based on previous research on the use of telemedicine in the community, it is still necessary to adjust preferences based on age, knowledge, and practice of implementing telemedicine. Therefore, our study contributes to exploring and estimating the variables related to continued telemedicine adoption. In addition, we also explore knowledge, administration, and data confidentiality factors in the performance of telemedicine services. On the knowledge factor, the questionnaire questions included the types of services available on telemedicine, how to use these services, and the reasons for using telemedicine applications. The knowledge factor questions are six questions. Meanwhile, regarding health administration factors, we asked three questions related to perceptions of the importance of ease of administration, the importance of recording service access history, and the importance of minimizing document requirements for telemedicine services through yes or no statements. Finally, on the data confidentiality factor, three questionnaire questions cover the responsibility for data confidentiality and perceptions of personal data security when using telemedicine services.

Before conducting an in-depth analysis, researchers coded the answers to classify the data and simplify the data entry process. The data then goes through a data entry process. All data underwent a normality test with the Kolmogorov-Smirnov test (). Thus, we found that the dependent and independent variable scores were not normally distributed ( value =0.001). Therefore, we used medians for cut-offs for all variables. The median value for the variable knowledge is 6, administration and data confidentiality is 3, and for the use of telemedicine is 24. This study only focused on a few independent variables, which are crucial in discussing telemedicine usage.

2.4. Data Analysis

The data in the questionnaire is inputted into the Microsoft Excel Worksheet (.xlsx) and then inputted into the SPSS 26.0 application to assess the findings. We utilized univariate analysis to explain the characteristics of respondents (such as gender, age, occupation, education, type of telemedicine used by respondents, frequency of telemedicine, and activities often carried out while using telemedicine). It is necessary to describe certain patterns and tendencies among telemedicine users. Bivariate analysis was used to determine the relationship between the dependent and independent variables, and the analysis used was Chi-square analysis. It could give a proper explanation regarding factors that pushed people to utilize telemedicine. Furthermore, to see the most dominant factors influencing the use of telemedicine, the researchers also used regression analysis.

3. Results

3.1. Demographic Features of Respondents

Based on the data we collected through questionnaires, most of our respondents were women, namely, 251 respondents or around 62.8%, while the rest were men, 149 respondents (37.3%). While on the age factor, generally, 18-30, namely, 321 respondents (80.3%), and respondents aged <18 years, 31-40 years, and >40 years, each less than 10%. Students dominate the respondents. We define a student as someone who goes through a learning process at all levels of formal education. A total of 340 respondents (85%) were students, 20 respondents (5%) were private employees, five respondents (1.3%) were self-employed, two housewives (0.5%), and two government officials (0.5%). Thirty-one respondents (7.8%) are not included in the previously mentioned occupational groups. Respondents in general (365 respondents or 91.3%) had a high school education, 8.3% (33 respondents) had a bachelor’s degree, and the remaining 0.5% (2 respondents) had a master’s degree (Table 1).

One of the platforms in telemedicine services still being used by the public is Halodoc (39.8%), a franchise provided by the private sector. Meanwhile, the services provided by the government, namely, mobile JKN, still need to be used by the public in this study, namely, only 0.3% of the total respondents. Respondents also use Alodokter (5.3%), KlikDokter (1%), and other franchises that require explicit identification (2.5%). The majority of respondents stated that they no longer used telemedicine (51.3%), while 10% of respondents stated that they still used it once a month, and the frequency was more than once a month and less than or equal to three times a year, each less than 10%. They all have experience using telemedicine, primarily for consulting doctors (30%), while their other activities are reading health articles (26.5%), buying medicine (9.5%), laboratory testing (2%), getting COVID-19 medicine for free (1.6%), and other telemedicine activities (30.5%) (Table 1).

3.2. Factors Influencing Perceptions of Telemedicine Implementation

We also performed the table relationship analysis in Table 2. We conducted a Chi-square test between the variables of perception of administration, data security, and respondents’ knowledge of the variable of perception of implementing telemedicine. Regarding data security actors, 199 respondents (49.75%) stated that their data security was secured. Among them, 47.7% of them stated that the implementation of telemedicine was good, and 52.3% said it was poor. Whereas 50.25% of respondents stated that the security of their data was not guaranteed, 56.7% of them stated that the implementation of telemedicine was good, while the rest stated the opposite. The relationship between the two variables has a value of 0.09 ( value >0.05). Thus, the two variables do not have a significant relationship.

Researchers could not conduct a Chi-square statistical test on administrative factors because all respondents (100%) stated that administration was good. However, the percentage of respondents’ opinions regarding the implementation of telemedicine is slightly different. Namely, 52.3% said it was good, and 47.8% said it was poor. Meanwhile, the knowledge variable related to the application of telemedicine has a value of 0.043 ( value <0.05) or is significantly related. Dominant respondents had good knowledge (290 respondents), where 49% considered the implementation of telemedicine to be good, and 51% stated that the implementation of telemedicine was poor. Meanwhile, 110 respondents had poor knowledge, of which 60.69% of respondents considered the implementation of telemedicine to be good, and 39.1% of respondents stated that the implementation of telemedicine was poor. The next step is to select significant variables ( value <0.05) based on the Chi-square test results and enter them into the regression test. Thus, the regression test can only be carried out on one variable that meets the significant requirements, namely, the knowledge variable.

The regression analysis results in Table 3 show that the knowledge variable produces a value of 0.03 ( value <0.05). In other words, knowledge has a significant relationship with perceptions regarding the application of telemedicine. The odds ratio value indicates that people with better knowledge will have the opportunity to utilize telemedicine services by 1.624 times (95% confidence interval). At the same time, the value of indicates that knowledge has a positive correlation with the use of telemedicine.

4. Discussion

Telemedicine is one of the targets of world technological progress [28, 29] in aspects of alternative health services [30, 31] that are safe, efficient, and effective in meeting patient needs [24]. Telemedicine is suitable for conditions that are not urgent and do not require an extensive physical examination [32]. Healthcare workers can use technology to contact patients, such as the telephone [33], or other telecommunications media, such as electronic health records, social alarms, and online client portals used in medicine [34].

The application of telemedicine involves a complex integration between information technology and healthcare services that enables service providers to diagnose, consult, and treat patients without geographic boundaries. By leveraging online platforms and dedicated applications, telemedicine revolutionizes traditional healthcare delivery while maintaining high medical standards. In the context of a global pandemic and increasing demand for medical services, telemedicine is increasingly becoming an essential solution in overcoming barriers to access and improving the quality of medical services in general [6, 14, 35, 36].

Specifically in Indonesia, this study’s results indicate that telemedicine use still needs to be increased. Currently, there is only one telemedicine franchise that dominates the Indonesian market, namely, Halodoc. This finding implies that telemedicine, the style of today’s digital devices, is not yet as prevalent among the public. Services of telemedicine include administration, information, and treatment. Our research results also show that most respondents were women, and most came from the younger generation, especially those aged 18-30. This finding is similar to other studies, with the average age of research respondents being 29 years [32] and other findings that telemedicine is suitable for the younger generation [17, 20], who are also more familiar with the use of technology and are open-minded in accessing modern health services. This study’s results also show the younger generation’s interest in telemedicine applications.

This condition is different in people with old age. Our findings align with Jaron in Poland, who found that the age group 60 years and over showed reluctance to access teleconsultation [37]. Telemedicine can only partially replace inpatient services, especially in people with old age. Telemedicine services should adapt according to patient needs to reduce obstacles and problems in this system, such as making long-distance visits to reassure the public [38]. Older patients can also use simple technological devices such as tablets which can make it easier to connect with doctors accompanied by counseling patients and preparing health experts or unique technology to deal with elderly patients and help them how to use digital devices [37].

Health services that use more than one service modality, such as distance medicine, have the potential to report higher utilization rates of health services compared to those that only have one service modality [33]. However, our study found that its application still faces challenges, particularly in the context of our research in Indonesia. Our research has found that this is because several barriers, including knowledge, can stop people from using this technology. While today’s technology, namely, telemedicine, can be associated with the younger generation, this was not always the case, as the barriers identified can create problems in the future. In this study, we found that knowledge is one of them. The results of our research explain that the better a person’s knowledge, the better access to telemedicine, with our respondents being high school graduates (91.3%) with student status (85%) or, in other words, continuing their education. This finding is in line with other research, which found a need for more telemedicine-related knowledge among research respondents who were also students [39, 40].

One study stated that telehealth investments could increase the utilization of youth health services and help maintain relationships with adolescents during shocks, including during a pandemic or other conditions that can limit physical access to health services [33]. The success of any use of new technology in the health sector depends on the user's knowledge, perception, and skills regarding the concept of program implementation [41]—digital skills of health workers and skills of patients [33]; attitude; and environment [40]; physical limitations of the patient; patient's cognitive limitations; sociodemographic and clinical characteristics of patients [34]; limitations of service provider diagnosis and management; perception of high costs (especially for mental health services) [32]; and language barriers [42]. There are specific legal, cultural, and social challenges [43]. Medical personnel are also concerned about possible emergencies due to limited patient visualization during telephone consultations. However, with telemedicine, health workers can perform triage, refer patients to health services, treat patients virtually, or perform a consultation [17]. Approaches to implementing telemedicine services vary, mainly based on the patient’s attitude, age, and adaptation needs [38]. In such circumstances, telemedicine can potentially exacerbate health inequities [37]. Policymakers must identify barriers among special populations to using telemedicine. They should initiate interventions to overcome these barriers while adapting them to the needs of this group [37]. Telemedicine can increase the number of patients who do not complete necessary laboratory and other tests [29].

Previous research found that there is avoidance of using relatively new services because people do not trust and benefit from these services [44–46]. On the other hand, other studies have found that telemedicine can answer health problems before and even after the COVID-19 pandemic [47–49]. Therefore, the government should provide education to the public about the use of telemedicine. Our findings show that the government-provided telemedicine platform is less popular with the public. Thus, as the primary stakeholder, the government must prepare new efforts. Other studies have also noted that people still perceive telemedicine as an “alternative” way to meet their health needs [2, 3, 46, 48, 49].

According to another study, the number of respondents with good knowledge as much as 67.4% of respondents had also received health information from the Internet as much as 23.6%, and 60.59% of respondents had visited telemedicine platforms. Respondents stated that they often exchange information about the COVID-19 virus via telemedicine as much as 75.3% and usually use communication services via telephone as much as 30.6% [50]. This finding is also consistent with other research, which found that the higher the respondent’s education, the higher the person has knowledge. At the same time, our research results found that the value was 0.015, which means that education affects the level of knowledge. Adequate knowledge is essential to encourage someone to try something new. Therefore, people must find ways to increase digital literacy to keep up with the increasingly sophisticated times [36, 51].

Due to our findings, we suggest increasing capacity building for citizens, positive medical or academic training, and continuing medical education for more complex diagnoses, which also play a small but integral role in video and web conferencing. This training can become a global learning forum by recording and broadcasting the learning sessions so that other doctors or students can access them for free. Additionally, facilitating the transfer of medical knowledge from sources in research centers using audiovisual and digital tools reduces the information gap for healthcare providers in underserved hospitals [47]. In other words, increasing digital literacy among young adults will create a tendency to take advantage of new technologies, especially those that benefit them.

Based on the results of our study, the data security variable has a value of 0.090 (>0.05), which means it does not affect the use of telemedicine. However, data security is an essential variable in telemedicine technology. In order for users to feel comfortable and continue to use the telemedicine platform, service providers must provide data security that is confidential and accurate [3, 18, 49, 52]. One form of data security that a telemedicine platform must facilitate is access control. Access control is a critical security solution to restrict unauthorized users from accessing one’s services. Access control is an essential tool for healthcare related to patients’ health and living conditions. In addition to access control, service providers must also utilize cryptographic technology. Cryptography has been widely used as an essential security solution to ensure several security requirements, such as confidentiality and data integrity [53].

Indeed, telemedicine has many advantages but can only partially replace the primary doctor-patient relationship. Some treatments would be more optimal in person, not just virtually. However, telemedicine is aimed at providing online counseling [54] and general healthcare services for various nonemergency general health conditions, including allergies, respiratory infections, skin rashes, sinus problems, migraines, and others [53–57]. Thus, it is necessary to expand the range of families or patients who can benefit and optimize patient care [58]. Ultimately, we still have to pay attention to the advantages and disadvantages of telemedicine. In short, telemedicine is more valuable for ensuring citizens’ health than focusing on various diseases. During the pandemic, telemedicine provided a way for people to meet their medical needs, which implies that technology can solve some critical problems, especially during emergencies. Meanwhile, public awareness of health is critical. The government and multisectors must be able to carry out collaborative interventions to strengthen awareness [59]. Collaborating with the community is one strategy that can help increase awareness of participation [60]. Apart from that, it is also essential to focus on increasing knowledge. Increasing knowledge is essential because it is closely related to individual attitudes [61, 62], encouraging increased awareness. Without adequate knowledge, people tend not to use new technology, even though the technology can provide benefits.

5. Conclusions

The use of telemedicine has increased significantly during the COVID-19 pandemic. Our findings highlight knowledge as the most crucial variable. Good knowledge does not necessarily have implications for good perceptions of telemedicine implementation. In other words, telemedicine technology needs to be updated to attract its users’ interest. Meanwhile, we also found telemedicine users with poor knowledge. Thus, education regarding this technology must be increased so that users are accustomed to using it. Knowledge of telemedicine will enable them to use it wisely. In addition, our research implies that health awareness fundamentally extends beyond knowledge of technology. With a proper understanding of the importance of health, society will look for ways to direct it toward it. In addition, social barriers in society cause their reluctance or inability to access valuable technologies such as telemedicine. Further research on telemedicine may explore these barriers. In addition, it is also essential for future researchers to focus on the effectiveness of telemedicine as a technology that functions to increase public health awareness and not only focus on the ability or effectiveness of telemedicine as a technology to cure disease.

Data Availability

The data and material of this article are not publicly available due to ethical matters but are available from the corresponding author on reasonable requests.

Ethical Approval

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Research Ethics Committee, Faculty of Medicine, Universitas Sebelas Maret (protocol code 161/UN27. 06.11/KEP/EC/2022 and date of approval on 21 November 2022).

Conflicts of Interest

The authors declared that there is no conflict of interest regarding the publication of this paper.

Acknowledgments

This work was supported by the Hibah Publikasi Terindeks Internasional (PUTI) Q2, Directorate of Research and Development, Universitas Indonesia (grant numbers NKB-1363/UN2.RST/HKP.05.00/2022).

References

M. S. Price, H. Christensen, J. Urquhart, S. Butte, R. Acierno, and D. M. Little, “Patient-facing, semi-automated, solutions to enhance patient participation in measurement-based care practice standards in a tele-mental health specialty clinic for populations at higher risk for self-harm,” International Journal of Medical Informatics, vol. 177, article 105155, 2023.
View at: Publisher Site | Google Scholar
D. Nacarato, A. V. Sardeli, L. O. Mariano, and M. P. Chacon-Mikahil, “Cardiovascular telerehabilitation improves functional capacity, cardiorespiratory fitness and quality of life in older adults: a systematic review and meta-analysis,” Journal of Telemedicine and Telecare, vol. 2022, 2020.
View at: Publisher Site | Google Scholar
S. Patel, S. Hamdan, and S. Donahue, “Optimising telemedicine in ophthalmology during the COVID-19 pandemic,” Journal of Telemedicine and Telecare, vol. 28, no. 7, pp. 498–501, 2022.
View at: Publisher Site | Google Scholar
A. H. Qari, R. M. Alharbi, S. S. Alomiri, B. N. Alandanusii, L. A. Mirza, and M. H. Al-Harthy, “Patients’ experience with teledentistry compared to conventional follow-up visits in TMD clinic: a pilot study,” Journal of Dentistry, vol. 140, Article ID 104774, 2024.
View at: Publisher Site | Google Scholar
R. P. Pierce and J. J. Stevermer, “Disparities in the use of telehealth at the onset of the COVID-19 public health emergency,” Journal of Telemedicine and Telecare, vol. 29, no. 1, pp. 3–9, 2023.
View at: Publisher Site | Google Scholar
M. A. Hincapié, J. C. Gallego, A. Gempeler, J. A. Piñeros, D. Nasner, and M. F. Escobar, “Implementation and usefulness of telemedicine during the COVID-19 pandemic: a scoping review,” Journal of Primary Care & Community Health, vol. 11, article 215013272098061, 2020.
View at: Publisher Site | Google Scholar
V. M. Gallegos-Rejas, E. E. Thomas, J. T. Kelly, and A. C. Smith, “A multi-stakeholder approach is needed to reduce the digital divide and encourage equitable access to telehealth,” Journal of Telemedicine and Telecare, vol. 29, no. 1, pp. 73–78, 2023.
View at: Publisher Site | Google Scholar
E. E. Thomas, H. M. Haydon, A. Mehrotra et al., “Building on the momentum: sustaining telehealth beyond COVID-19,” Journal of Telemedicine and Telecare, vol. 28, no. 4, pp. 301–308, 2022.
View at: Publisher Site | Google Scholar
K. Nakagawa and P. Yellowlees, “Inter-generational Effects of Technology: Why Millennial Physicians May Be Less at Risk for Burnout Than Baby Boomers,” Current Psychiatry Reports, vol. 22, no. 9, p. 45, 2020.
View at: Publisher Site | Google Scholar
Y. N. Evans, S. Golub, G. M. Sequeira, E. Eisenstein, and S. North, “Using telemedicine to reach adolescents during the COVID-19 pandemic,” Journal of Adolescent Health, vol. 67, no. 4, pp. 469–471, 2020.
View at: Publisher Site | Google Scholar
WHO, “Implementing telemedicine services during COVID-19: guiding principles and considerations for a stepwise approach,” 2020, https://apps.who.int/iris/handle/10665/336862.
View at: Google Scholar
F. Sasangohar, E. Davis, B. A. Kash, and S. R. Shah, “Remote patient monitoring and telemedicine in neonatal and pediatric settings: scoping literature review,” Journal of Medical Internet Research, vol. 20, no. 12, article e295, 2018.
View at: Google Scholar
L. Hawrysz, G. Gierszewska, and A. Bitkowska, “The research on patient satisfaction with remote healthcare prior to and during the COVID-19 pandemic,” International Journal of Environmental Research and Public Health, vol. 18, no. 10, p. 5338, 2021.
View at: Publisher Site | Google Scholar
M. Zimmerman, I. Benjamin, J. W. Tirpak, and C. D'Avanzato, “Patient satisfaction with partial hospital telehealth treatment during the COVID-19 pandemic: comparison to in-person treatment,” Psychiatry Research, vol. 301, article 113966, 2021.
View at: Publisher Site | Google Scholar
Kementerian Kesehatan Republik Indonesia, “Kemenkes sediakan layanan telekonsultasi dan paket obat gratis bagi pasien isoman terkonfirmasi Omicron,” 2022, https://sehatnegeriku.kemkes.go.id/baca/rilis-media/20220124/2039210/kemenkes-sediakan-layanan-telekonsultasi-dan-paket-obat-gratis-bagi-pasien-isoman-terkonfirmasi-omicron/.
View at: Google Scholar
D. D. Payán, J. L. Frehn, L. Garcia, A. A. Tierney, and H. P. Rodriguez, “Telemedicine implementation and use in community health centers during COVID-19: clinic personnel and patient perspectives,” SSM-Qualitative Research in Health, vol. 2, article 100054, 2022.
View at: Publisher Site | Google Scholar
P. M. Galagali, S. Ghosh, and H. Bhargav, “The role of telemedicine in child and adolescent healthcare in India,” Current Pediatrics Reports, vol. 9, no. 4, pp. 154–161, 2021.
View at: Publisher Site | Google Scholar
K. Mahmoud, C. Jaramillo, and S. Barteit, “Telemedicine in low- and middle-income countries during the COVID-19 pandemic: a scoping review,” Frontiers in Public Health, vol. 10, article 914423, 2022.
View at: Publisher Site | Google Scholar
M. Y. Abuhashesh, H. Al-Dmour, R. Masa’deh et al., “The role of social media in raising public health awareness during the pandemic COVID-19: an international comparative study,” Informatics, vol. 8, no. 4, p. 80, 2021.
View at: Publisher Site | Google Scholar
J. Pool, S. Akhlaghpour, F. Fatehi, and L. C. Gray, “Data privacy concerns and use of telehealth in the aged care context: an integrative review and research agenda,” International Journal of Medical Informatics, vol. 160, article 104707, 2022.
View at: Publisher Site | Google Scholar
E. Gil-Olivas, F. Salvador, M. Moreno et al., “Telemedicine experience between two hospitals from Angola and Spain,” International Journal of Technology Assessment in Health Care, vol. 36, no. 6, pp. 545–548, 2020.
View at: Publisher Site | Google Scholar
L. L. Corona, A. S. Weitlauf, J. Hine et al., “Parent perceptions of caregiver-mediated telemedicine tools for assessing autism risk in toddlers,” Journal of Autism and Developmental Disorders, vol. 51, pp. 476–486, 2021.
View at: Publisher Site | Google Scholar
C. Leonard, W. Liu, A. Holstein et al., “Informing use of telehealth for managing chronic conditions: Mixed‐Methods evaluation of telehealth use to manage heart failure during COVID-19,” Journal of the American Heart Association, vol. 12, no. 4, article e027362, 2023.
View at: Publisher Site | Google Scholar
T. H. Broens, R. M. H. A. Huis in't Veld, M. M. R. Vollenbroek-Hutten, H. J. Hermens, A. T. van Halteren, and L. J. M. Nieuwenhuis, “Determinants of successful telemedicine implementations: a literature study,” Journal of Telemedicine and Telecare, vol. 13, no. 6, pp. 303–309, 2007.
View at: Publisher Site | Google Scholar
K. A. Shamiyah, S. Whitebridge, N. Kumar, K. Aljenaee, S. L. Atkin, and K. F. Ali, “The impact of COVID-19 on the prevalence and perception of telehealth use in the Middle East and North Africa region: survey study,” JMIR Form Research, vol. 7, article e34074, 2023.
View at: Publisher Site | Google Scholar
R. D. Smit, N. Mouchtouris, M. Reyes et al., “The use of telemedicine in pre-surgical evaluation: a retrospective cohort study of a neurosurgical oncology practice,” Journal of Neuro-Oncology, vol. 159, no. 3, pp. 621–626, 2022.
View at: Publisher Site | Google Scholar
M. Cottrell, C. L. Burns, A. Jones et al., “Sustaining allied health telehealth services beyond the rapid response to COVID-19: learning from patient and staff experiences at a large quaternary hospital,” Journal of Telemedicine and Telecare, vol. 27, no. 10, pp. 615–624, 2021.
View at: Publisher Site | Google Scholar
M. Alvarez-Jimenez, S. Rice, S. D'Alfonso et al., “A novel multimodal digital service (moderated online social therapy+) for help-seeking young people experiencing mental ill-health: pilot evaluation within a national youth E-mental health service,” Journal of Medical Internet Research, vol. 22, no. 8, article e17155, 2020.
View at: Publisher Site | Google Scholar
I. AlFawaz and A. A. Alrasheed, “Experiences with telemedicine among family medicine residents at King Saud University Medical City during the COVID-19 pandemic: a cross-sectional study,” BMC Medical Education, vol. 23, no. 1, article 313, 2023.
View at: Publisher Site | Google Scholar
C. Sacchi, K. Andersson, M. Roczniewska et al., “Mind the gap: analysis of two pilot projects of a home telehealth service for persons with complex conditions in a Swedish hospital,” BMC Health Services Research, vol. 23, no. 1, p. 463, 2023.
View at: Publisher Site | Google Scholar
F. Parlindungan, S. Sumariyono, R. Hidayat et al., “Learning from the COVID-19 pandemic: health care disturbances and telemedicine as an alternative rheumatology practice in Indonesia,” BMC Health Services Research, vol. 23, no. 1, article 451, 2023.
View at: Publisher Site | Google Scholar
A. V. G. Noceda, L. M. M. Acierto, M. C. C. Bertiz et al., “Patient satisfaction with telemedicine in the Philippines during the COVID-19 pandemic: a mixed methods study,” BMC Health Services Research, vol. 23, no. 1, p. 277, 2023.
View at: Publisher Site | Google Scholar
A. Okunogbe, M. Meekins, K. Saalim et al., “Utilization of adolescent health services during the COVID-19 pandemic: evidence on impact and adaptations from a rapid assessment survey in the Philippines,” BMC Public Health, vol. 23, no. 1, p. 493, 2023.
View at: Publisher Site | Google Scholar
E. Mathijssen, W. de Lange, N. Bleijenberg et al., “Factors that influence the use of eHealth in home care: scoping review and cross-sectional survey,” Journal of Medical Internet Research, vol. 25, article e41768, 2023.
View at: Publisher Site | Google Scholar
D. A. Back, K. Estel, D. Pförringer et al., “Implementation of online video consultations in a regional health network: a management feasibility analysis from an orthopedic perspective,” BMC Health Services Research, vol. 22, no. 1, p. 1029, 2022.
View at: Publisher Site | Google Scholar
H.-P. Cremers, L. Theunissen, J. Hiddink et al., “Successful implementation of ehealth interventions in healthcare: development of an ehealth implementation guideline,” Health Services Management Research, vol. 34, no. 4, pp. 269–278, 2021.
View at: Publisher Site | Google Scholar
M. Haimi, “The tragic paradoxical effect of telemedicine on healthcare disparities- a time for redemption: a narrative review,” BMC Medical Informatics and Decision Making, vol. 23, no. 1, p. 95, 2023.
View at: Publisher Site | Google Scholar
K. Jaroń, A. Jastrzębska, K. Mąkosza, M. Grajek, K. Krupa-Kotara, and J. Kobza, “Availability of medical services and teleconsultation during COVID-19 pandemic in the opinion of patients of hematology clinics—a cross-sectional pilot study (Silesia, Poland),” International Journal Environmental Research and Public Health, vol. 20, no. 5, p. 4264, 2023.
View at: Publisher Site | Google Scholar
F. M. García-Gutiérrez, F. Pino-Zavaleta, M. A. Romero-Robles et al., “Self-reported perceptions and knowledge of telemedicine in medical students and professionals who enrolled in an online course in Peru,” BMC Medical Education, vol. 23, no. 1, p. 88, 2023.
View at: Publisher Site | Google Scholar
K. Ghaddaripouri, S. F. M. Baigi, A. Abbaszadeh, and M. R. M. Habibi, “Attitude, awareness, and knowledge of telemedicine among medical students: a systematic review of cross-sectional studies,” Health Science Reports, vol. 6, no. 3, article e1156, 2023.
View at: Publisher Site | Google Scholar
S. Raes, L. Annemans, R. Willems, and J. Trybou, “Physicians’ views on optimal use and payment system for telemedicine: a qualitative study,” BMC Health Services Research, vol. 23, no. 1, p. 292, 2023.
View at: Publisher Site | Google Scholar
K. M. Fitzpatrick, M. Ody, D. Goveas et al., “Understanding virtual primary healthcare with indigenous populations: a rapid evidence review,” BMC Health Services Research, vol. 23, no. 1, p. 303, 2023.
View at: Publisher Site | Google Scholar
A. S. Pinto, A. Abreu, E. Costa, J. Paiva, and L. Vieira, “Adoption of telemedicine during the COVID-19 pandemic in Ibero-America: a systematic literature review,” Journal of Information Systems Engineering and Management, vol. 8, no. 1, article 19138, 2023.
View at: Publisher Site | Google Scholar
T. Ein-Dor, “Facing danger: how do people behave in times of need? The case of adult attachment styles,” Frontiers in Psychology, vol. 5, 2014.
View at: Publisher Site | Google Scholar
V. Yee, S. S. Bajaj, and F. C. Stanford, “Paradox of telemedicine: building or neglecting trust and equity,” The Lancet Digital Health, vol. 4, no. 7, pp. E480–E481, 2022.
View at: Publisher Site | Google Scholar
M. Lyu, Q. Zhao, Y. Yang, X. Hao, Y. Qin, and K. Li, “Benefits of and barriers to telehealth for the informal caregivers of elderly individuals in rural areas: a scoping review,” Australian Journal of Rural Health, vol. 30, no. 4, pp. 442–457, 2022.
View at: Publisher Site | Google Scholar
E. Eisenstein, C. Kopacek, S. S. Cavalcante, A. C. Neves, G. P. Fraga, and L. A. Messina, “Telemedicine: a bridge over knowledge gaps in healthcare,” Current Pediatrics Reports, vol. 8, no. 3, pp. 93–98, 2020.
View at: Publisher Site | Google Scholar
J. C. Lin, M. D. Humphries, W. P. Shutze, O. O. Aalami, U. M. Fischer, and K. J. Hodgson, “Telemedicine platforms and their use in the coronavirus disease-19 era to deliver comprehensive vascular care,” Journal of Vascular Surgery, vol. 73, no. 2, pp. 392–398, 2021.
View at: Publisher Site | Google Scholar
M. L. Taylor, E. E. Thomas, K. Vitangcol et al., “Digital health experiences reported in chronic disease management: an umbrella review of qualitative studies,” Journal of Telemedicine and Telecare, vol. 28, no. 10, pp. 705–717, 2022.
View at: Publisher Site | Google Scholar
B. T. Assaye and A. W. Shimie, “Telemedicine use during COVID-19 pandemics and associated factors among health professionals working in health facilities at resource limited setting 2021,” Informatics in Medicine Unlocked, vol. 33, article 101085, 2022.
View at: Publisher Site | Google Scholar
M. Alboraie, M. A. Allam, N. Youssef et al., “Knowledge, applicability, and barriers of telemedicine in Egypt: a national survey,” International Journal of Telemedicine and Applications, vol. 2021, Article ID 5565652, 8 pages, 2021.
View at: Publisher Site | Google Scholar
J. J. Reeves, J. W. Ayers, and C. A. Longhurst, “Telehealth in the COVID-19 era: a balancing act to avoid harm,” Journal of Medical Internet Research, vol. 23, no. 2, article e24785, 2021.
View at: Publisher Site | Google Scholar
S.-R. Oh, Y.-D. Seo, E. Lee, and Y.-G. Kim, “A comprehensive survey on security and privacy for electronic health data,” International Journal of Environmental Research and Public Health, vol. 18, no. 18, p. 9668, 2021.
View at: Publisher Site | Google Scholar
T. Y. R. Pristya, C. K. Herbawani, U. Q. Karima, A. Oktafiyanti, N. Ramadhanty, and A. Ginawang, “Perception of covid-19 and reproductive health of female and male ADOLESCENT in urban areas in the Sustainable Development Goals,” Journal of Environmental Science and Sustainable Development, vol. 5, no. 1, pp. 130–148, 2022.
View at: Publisher Site | Google Scholar
S. K. Mistry, F. Akter, U. N. Yadav et al., “Factors associated with mobile phone usage to access maternal and child healthcare among women of urban slums in Dhaka, Bangladesh: a cross-sectional study,” BMJ Open, vol. 11, no. 4, article e043933, 2021.
View at: Publisher Site | Google Scholar
H. Al-Dmour, R. Masa’deh, A. Salman, M. Abuhashesh, and R. Al-Dmour, “Influence of social media platforms on public health protection against the COVID-19 pandemic via the mediating effects of public health awareness and behavioral changes: integrated model,” Journal of Medical Internet Research, vol. 22, no. 8, article e19996, 2020.
View at: Publisher Site | Google Scholar
A. R. Westwood, “Is hybrid telehealth model the next step for private healthcare in India?” Health Services Insights, vol. 14, article 117863292110433, 2021.
View at: Publisher Site | Google Scholar
T. Troschke, A. Wieczorek, K. Kulinski et al., “Pediatric hematology and oncology center integrated by telemedicine: experience, challenges and first results of a cross border network,” Healthcare, vol. 11, no. 10, p. 1431, 2023.
View at: Publisher Site | Google Scholar
N. Nuraeni, I. Hawa, D. Utari, and E. Parahyanti, “Clean and healthy environmental behavior in terms of malnutrition and sanitation,” Global Journal of Environmental Science and Management, vol. 10, no. 2, pp. 1–16, 2024.
View at: Google Scholar
H. Herdiansyah, “Smart city based on community empowerment, social capital, and public trust in urban areas,” Global Journal of Environmental Science and Management, vol. 9, no. 1, pp. 113–128, 2023.
View at: Google Scholar
D. Utari, N. I. Hawa, G. Fizulmi, and H. Agustina, “Evaluation of community behavior regarding the risk of plastic micro-pollution on the environment health,” Global Journal of Environmental Science and Management, vol. 10, no. 2, pp. 1–16, 2024.
View at: Google Scholar
H. Herdiansyah and Nuraeni, “Environmental awareness and plastic use behavior during the COVID-19 pandemic,” Global Journal of Environmental Science and Management, vol. 10, no. 2, pp. 1–16, 2024.
View at: Google Scholar

Copyright

Copyright © 2023 Nada I. Hawa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

246

Downloads

214

Citations