Research Article
Print
Research Article
Assessing knowledge, perceptions, and readiness of telemedicine recipients: A cross-sectional study
expand article infoIman Hamdan‡, Enas Alkhader‡
‡ Middle East University, Amman, Jordan

Corresponding author: Iman Hamdan ( ihamdan@meu.edu.jo )

Academic editor: Valentina Petkova
© 2024 Iman Hamdan, Enas Alkhader.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Hamdan I, Alkhader E (2024) Assessing knowledge, perceptions, and readiness of telemedicine recipients: A cross-sectional study. Pharmacia 71: 1-6. https://doi.org/10.3897/pharmacia.71.e122134
Open Access

Abstract

Objectives: The current study aimed to assess the knowledge and perceptions of telemedicine recipients. Secondly, to evaluate their readiness towards adopting telemedicine in clinical settings.

Methods: A cross-sectional survey study was conducted in Jordan and designed to show the demographics of participants. The questionnaire was piloted for validity and reliability to achieve the aim of the study, and a collective of 420 participants were recruited.

Findings: Multiple regression analysis conducted showed that telemedicine services were significant at a level of α ≤ 0.05. Whereas the Pearson’s correlation of the dependent and independent variables was also significant at a level of α ≤ 0.05 as a function of age, working status, and income.

Conclusions: Regardless of the fact that participants showed a limited knowledge of telemedicine services, most of the participants expressed positive perceptions towards telemedicine services and its adoption in the clinical settings.

Keywords

Telemedicine, Telemedicine recipients, Knowledge, Perceptions, Readiness

Introduction

Although the healthcare system has undergone a remarkable change in recent years, still, some areas need reform (Campion et al. 2016; Barbosa et al. 2021). A major dilemma confronting healthcare systems nowadays is to sustain capacity and improve access (Barbosa et al. 2021; Burau et al. 2022; Chauhan et al. 2024) to provide medical services to patients without compromising the safety of the healthcare providers as well as patients, especially in circumstances where so-called social distancing in a clinical setting is pressing (Bashshur et al. 2020; Ftouni et al. 2022; Wilhite et al. 2022). Telemedicine is an emerging tool that has the potential to provide more effective, organized, and accessible healthcare services at the convenience of both patients and healthcare providers. (Bashshur et al. 2020; Haleem et al. 2021; Bell-Aldeghi et al. 2023). It concerns with providing medical information, teleconsultation, and telediagnosis remotely (Clark et al. 2010; Witkowski et al. 2016; Hassan et al. 2019; Cui et al. 2020; Peltan et al. 2020; Ando et al. 2022). Teleconsultation is notably of paramount importance in the prevention of diseases that hold unnoticeable symptoms to patients (Carrillo de Albornoz et al. 2022; Furlepa et al. 2022). Telemedicine is the merging between advanced technology, network and medical services (Lucas 2008; Haleem et al. 2021; Alenoghena et al. 2023) that has a great potential with the most significant effect on patients in remote areas (Freiburger et al. 2007; Lopez et al. 2021), and communities suffering from shortage or absence of healthcare services (Su et al. 2022). Telemedicine has proven to be reliable and cost-effective (Fong et al. 2011) as costs are comparable to that of face-to-face traditional visits (Nittari et al. 2020). Nevertheless, telemedicine confronts many challenges to its adoption which would vary depending on the country (Ammenwerth et al. 2003; Barlow et al. 2007; Cresswell and Sheikh 2013; Alaboudi et al. 2016; Albarrak et al. 2021). Telemedicine implementation would be hampered by various issues such as the lack of knowledge and incorrect perception by the public (Demartines et al. 2000; Ammenwerth et al. 2003; Meher et al. 2009; Cresswell and Sheikh 2013; Alaboudi et al. 2016). Therefore, it is essential to make the public comprehend the new idea of telemedicine and assess their willingness and readiness to adopt telemedicine services. The present study aims to evaluate the knowledge of telemedicine recipients about telemedicine and its applications. Furthermore, to assess their willingness and readiness towards adopting telemedicine.

Materials and methods

Study design

A cross-sectional study was carried out in Jordan between August, 2023 and January, 2024. The Survey method employed consisted of mixed mood questions type i.e. closed ended and scoring questions (Suppl. material 1, Sec 1), and designed to show the demographics of participants. The questionnaire was piloted for validity and reliability to achieve the aim of the study (Suppl. material 1, Sec 2). Reliability testing for stability and internal consistency were met and confirmed by Cronbach’s alpha (0.877) and Pearson’s correlation analysis. A voluntary simple random sampling strategy was adopted to collect the data. To estimate the expected response numbers, the sample size of participants was calculated using Eq.1, and a collective of 420 participants were recruited.

s = X2NP (1 − P) ÷ d2 (N − 1) + X2P (1 − P) Eq. 1

Where; s = required sample size, X2 = the table value of chi-square for 1 degree of freedom at the desired confidence level (3.841), N = the population size, P = the population proportion, and d = the degree of accuracy expressed as a proportion (0.05). The inclusion criteria were individuals aged 20 years old or above, willing to take part in the study. Participants were briefed on the study and invited to complete the online survey sent through social media. Before commencing the questionnaire, participants were informed that the completion of the questionnaire is voluntary and all the information obtained will be treated confidentially.

Study model

The study model was structured based on observations from literature (Bashshur et al. 2011; Cui et al. 2020; Nguyen et al. 2020; Nittari et al. 2020; Albarrak et al. 2021; Hajesmaeel-Gohari and Bahaadinbeigy 2021; Haleem et al. 2021; Furlepa et al. 2022), and interviewing professionals who have experience and expertise in this field. This study model consisted of four dimensions which are; A) telemedicine services, B) knowledge, C) perceptions, and D) readiness. The study hypothesis was developed as follows; (H01): recipients’ knowledge does not impact telemedicine services, at α ≤ 0.05, (H02): recipients’ perceptions do not relate to telemedicine services, at α ≤ 0.05, (H03): recipients’ readiness does not attribute to telemedicine services, at α ≤ 0.05. The questions rating was measured by five likert type scale; strongly disagree, disagree, neutral, agree, strongly agree.

Ethical approval

Ethical approval for the present study was granted by the Research Ethics Committee/Middle East University, Amman, Jordan; Reference number PD/E/2429.

Statistical analysis

Descriptive statistics (means, standard deviations, frequencies, and percentages) were generated using IBM SPSS (Statistical Package for Social Science) version 27. Where appropriate, different statistical analysis were performed to compare results such as; two sample (t-test), Pearson’s correlation test, one-way analysis of variant (ANOVA), multiple comparison (LSD) test, and Phi correlation test. The significance level was set at P < 0.05.

Results

Demographics

A total of 420 participants took part in this current study and were all from Jordan. About (47%) of the participants had health insurance, where (16%) suffered from chronic disease, and (7.4%) stated they have experienced telemedicine previously. The participants’ gender, age distribution, qualification, working status, and income are presented in Table 1.

Table 1.
Download as
CSV
XLSX

Demographic distribution of the study sample.

Type Frequency (N) Percent (%)
Gender
Male 169 40.2
Female 251 59.8
Age
20–30 164 39.0
31–40 128 30.5
41–50 113 26.9
> 50 15 3.6
Qualifications
High school 30 7.1
Diploma 56 13.3
Bachelors 280 66.7
Higher educational degrees 54 12.9
Working status
Employed/ self employed 306 72.9
Unemployed 106 25.2
Retired 8 1.9
Average income/ month
<500 $ 110 26.2
500–1000 $ 143 34.0
1001–1500 $ 61 14.5
>1500$ 14 3.3
Health insurance
Yes 197 46.9
Chronic diseases
Yes 67 16
Experienced telemedicine previously
Yes 31 7.4

Mean values, standard deviations, and one-way analysis of variant (ANOVA) test were calculated for the responses to the study dimensions as a function of age, qualifications, working status, and income. The resulting data showed that there were statistically significant differences (α < 0.05) in all dimensions as a function of age, which means that age, qualifications, working status, and income had an impact on the dependent and the independent variables of the study. Means and standard deviations were calculated for the study dimensions as show in Table 2. It was noted that the knowledge of telemedicine recipients is low and limited with a mean value of 2.1 ± 0.87. By contrast, perceptions and readiness of telemedicine recipients were positive and had a high score of mean values 4.1 ± 0.82, 4.0 ± 0.78, respectively.

Table 2.
Download as
CSV
XLSX

Means and standard deviations of the four study dimensions.

Dimensions N Mean Std. Deviation Assessment
Telemedicine services 420 4.1 0.76 High
Knowledge 420 2.1 0.87 Low
Perceptions 420 4.1 0.82 High
Readiness 420 4.0 0.78 High
Total 420 3.6 0.79 Medium

Multiple regression analysis was conducted between the independent and dependent variables i.e. knowledge, willingness, readiness of telemedicine recipients and telemedicine services as presented in Table 3. The resulting data showed that the dependent variable i.e. telemedicine services was significant at a level of α ≤ 0.05. The calculated F-value was (108.65) at a level of α ≤ 0.05, accordingly, the null hypothesis was rejected, and hence, there was a statically significant impact of knowledge, willingness, and readiness of telemedicine recipients on telemedicine services. The relationship between the dependent and independent variables was strong and positive with R value of 0.663. The higher significance was assigned to the willingness of recipients for telemedicine services with a t value of 9.9.

Table 3.
Download as
CSV
XLSX

Multiple regressions conducted for the study hypothesis.

Dependent variable R R2 F Sig. Independent variable Beta t Sig.
Telemedicine services 0.663 0.439 108.649 0.000*** Knowledge 0.114 3.463 <0.001***
Willingness 0.476 9.886 <0.001***
Readiness 0.173 3.395 <0.001***

R = correlation coefficient; R2 = coefficient of determination; F = F-statistic; Sig. = significance probability (p-value ≤ 0.05: statistically significant; p-value > 0.05 = not statistically significant); Beta = unstandardized coefficients; and t = test statistic for t-test.

Data presented in Table 4 showed that knowledge, willingness, and readiness of telemedicine recipients had a significant linear correlation with telemedicine services at a level of α ≤ 0.05. These correlations were also significant at a level of α ≤ 0.05 as a function of age, working status, and income. The Pearson’s correlation was strong with values of 0.64 and 0.52 assigned for willingness and readiness of telemedicine recipients towards telemedicine services, respectively. The latter illustrated that the demographics of participants had an impact on telemedicine services.

Table 4.
Download as
CSV
XLSX

Pearson’s correlation between independent and dependent variables.

Knowledge Willingness Readiness for Telemedicine
Overall correlation with the telemedicine technology
0.135 0.643 0.515
Impact of age on the telemedicine technology Sig.
20–30 years 0.227 0.153 0.023 <0.001***
31–40 years 0.142 0.101 0.049
41–50 years 0.094 0.049 0.013
> 50 years 0.020 0.035 0.028
Impact of working status on the telemedicine technology Sig.
Employed 0.212 0.145 0.116 <0.001***
Retired 0.070 0.076 0.052
Unemployed 0.239 0.173 0.135
Impact of income on the telemedicine technology Sig.
<500 $ 0.008 0.159 0.112 <0.001***
500–1000 $ 0.168 0.184 0.113
1001–1500 $ 0.034 0.072 0.065
> 1500 $ 0.088 0.050 0.080
No income 0.192 0.126 0.101

Discussion

This study explored the knowledge, perceptions, and readiness of patients towards the application of telemedicine services in Jordan. A total of 420 participants took part in the survey, and their demographics were captured (Table 1). There is scarcity in the existing literature in the region regarding telemedicine technology and services from recipients’ perspectives (AlBar and Hoque 2019; Baradwan and Al-Hanawi 2023), and hence, this was considered a focal point behind conducting this research so as to fill in the gaps in literature and generate a valuable database that holds a great value to stakeholders. Additionally, there is an urgent need to have deeper insights into the factors that hinder the advancement of telemedicine technology in Jordan, which once they are defined, would maximize the utility of healthcare services.

The current study showed the impact of sociodemographic factors on overall knowledge, perceptions and readiness of telemedicine recipients towards telemedicine services, except for gender and education variables (Table 4). The knowledge of telemedicine recipients towards telemedicine services was limited in Jordan (Table 2), and there is a need to specially target older adults and people who are retired, supported by their very low values of Pearson’s correlation coefficient; 0.02 and 0.07, respectively (Table 4). Some of these outcomes were in agreement with other studies conducted in Saudi Arabia and Indonesia for the same examined sociodemographic factors (Tjiptoatmadja and Alfian 2022; Baradwan and Al-Hanawi 2023), which may be attributed to cultural and regional differences. Our study illustrated that there was an association between age, working status, income and knowledge and perceptions towards telemedicine services (p < 0.001). Tjiptoatmadja and Alfian (2022), demonstrated that an association was observed between all demographics and knowledge of telemedicine except for gender. While there were no association between gender, age, education and perceptions towards telemedicine services (Tjiptoatmadja and Alfian 2022).

The surveyed participants’ knowledge of telemedicine services showed a low mean score 2.1 ± 0.87 (Table 2), however, was statistically significant (p < 0.001) (Table 3). One study demonstrated that around three-quarters of the participants had never heard about telemedicine (Baradwan and Al-Hanawi 2023), while another study showed that about half of the participants had heard about telemedicine services (Tjiptoatmadja and Alfian 2022). Despite the limited knowledge and the limited number of individuals who had actually used telemedicine services before, participants had positive perceptions and a readiness towards telemedicine services supported by the mean scores of 4.1 ± 0.82 and 4.0 ± 0.78, respectively, (Table 2). Both perceptions and readiness of participants were statistically significant towards telemedicine services at a level of α ≤ 0.05 (Table 3). Participants agreed to consult doctors while at home due to crowding in hospitals or when social distancing is recommended as in pandemics. In addition, participants would like to pay for the online-based healthcare services and to get training on how to use telemedicine technology (Suppl. material 1, Sec 1). Participants stated that they own technology devices such as; smartphones, tablets, or computers and internet connection at home. They expressed that they feel confident to download a telemedicine application and were ready to benefit from the services that telemedicine offers (Suppl. material 1, Sec 1). These findings were supported by a previous study in which participants showed a positive perception towards telemedicine services (Tjiptoatmadja and Alfian 2022; Baradwan and Al-Hanawi 2023). Participants had agreed that they would benefit from telemedicine services in terms of saving time, cost effectiveness, and comfort (Tjiptoatmadja and Alfian 2022; Baradwan and Al-Hanawi 2023). Another study reported that patients who received telemedicine healthcare services had acknowledged this experience (Holtz 2021). However, there were individuals who reported their concerns regarding the information privacy and unclear legal aspects of telemedicine practice (Baradwan and Al-Hanawi 2023). Telemedicine can provide distant, off-site, and interactive real-time consultations for patients (Zheng et al. 2018; Sharifi Kia et al. 2023), when an in-person visit is unnecessary. Virtual healthcare through telemedicine services may be considered as equally effective alternative to face-to-face visits. This may remove the necessity for work absences and so reduce the spread of infections among patients, which is especially risky for people suffering from chronic diseases or who are immunodeficient (Sarhan 2009; Bashshur et al. 2011; Funderskov et al. 2019; Rockwell and Gilroy 2020; Haleem et al. 2021). This technology permits patients to take repeat medications and be recalled for appointments (Lokkerbol et al. 2014). Numerous studies have investigated the usefulness of telemedicine in the treatment of various ailments such as diabetes and burns and many others (Zhai et al. 2014; Wang et al. 2017; Cheng et al. 2019).

Conclusions

Regardless of the fact that participants showed a limited knowledge of telemedicine services, most of the participants expressed positive perceptions towards telemedicine services and its adoption in clinical settings. Telemedicine can provide distant, off-site, and interactive real-time consultations for patients when an in-person visit is unnecessary. Virtual healthcare through telemedicine services may be considered as an equally effective alternative to face-to-face visits. Poor knowledge by end users, particularly patients, imposes an urgent need to increase awareness of telemedicine services in the healthcare domain to facilitate its adoption in Jordan. Interventions to increase knowledge of telemedicine in Jordan need to specially target older adults and people who are retired.

Acknowledgements

The author is grateful to pharmacist Bayan Saad for technical management of the project, and for data distribution and collection.

References

  • Ahmed Kamal M, Ismail Z, Shehata IM, Djirar S, Talbot NC, Ahmadzadeh S, Shekoohi S, Cornett EM, Fox CJ, Kaye AD (2023) Telemedicine, e-health, and multi-agent systems for chronic pain management. Clinics and Practice 13(2): 470–482. https://doi.org/10.3390/clinpract13020042
  • Alaboudi A, Atkins A, Sharp B, Balkhair A, Alzahrani M, Sunbul T (2016) Barriers and challenges in adopting Saudi telemedicine network: The perceptions of decision makers of healthcare facilities in Saudi Arabia. Journal of Infection and Public Health 9(6): 725–733. https://doi.org/10.1016/j.jiph.2016.09.001
  • AlBar AM, Hoque MR (2019) Patient acceptance of e-health services in Saudi Arabia: an integrative perspective. Telemedicine and e-Health 25(9): 847–852. https://doi.org/10.1089/tmj.2018.0107
  • Albarrak AI, Mohammed R, Almarshoud N, Almujalli L, Aljaeed R, Altuwaijiri S, Albohairy T (2021) Assessment of physician’s knowledge, perception and willingness of telemedicine in Riyadh region, Saudi Arabia. Journal of Infection and Public Health 14(1): 97–102. https://doi.org/10.1016/j.jiph.2019.04.006
  • Alenoghena CO, Ohize HO, Adejo AO, Onumanyi AJ, Ohihoin EE, Balarabe AI, Okoh SA, Kolo E, Alenoghena B (2023) Telemedicine: A survey of telecommunication technologies, developments, and challenges. Journal of Sensor and Actuator Networks 12(2): 20. https://doi.org/10.3390/jsan12020020
  • Ammenwerth E, Gräber S, Herrmann G, Bürkle T, König J (2003) Evaluation of health information systems—problems and challenges. International Journal of Medical Informatics 71(2–3): 125–135. https://doi.org/10.1016/S1386-5056(03)00131-X
  • Ando T, Mori R, Takehara K, Asukata M, Ito S, Oka A (2022) Effectiveness of pediatric teleconsultation to prevent skin conditions in infants and reduce parenting stress in mothers: randomized controlled trial. JMIR Pediatrics and Parenting 5(1): e27615. https://doi.org/10.2196/27615
  • Baradwan S, Al-Hanawi M (2023) Perceived knowledge, attitudes, and barriers toward the adoption of telemedicine services in the Kingdom of Saudi Arabia: cross-sectional study. JMIR Formative Research 7(1): e46446. https://doi.org/10.2196/46446
  • Barlow J, Singh D, Bayer S, Curry R (2007) A systematic review of the benefits of home telecare for frail elderly people and those with long-term conditions. Journal of Telemedicine and Telecare 13(4): 172–179. https://doi.org/10.1258/135763307780908058
  • Bashshur R, Doarn CR, Frenk JM, Kvedar JC, Woolliscroft JO (2020) Telemedicine and the COVID-19 pandemic, lessons for the future. Telemedicine and e-Health 26(5): 571–573. https://doi.org/10.1089/tmj.2020.29040.rb
  • Bell-Aldeghi R, Gibrat B, Rapp T, Chauvin P, Guern ML, Billaudeau N, Ould-Kaci K, Sevilla-Dedieu C (2023) Determinants of the cost-effectiveness of telemedicine: systematic screening and quantitative analysis of the literature. Telemedicine and e-Health 29(7): 1078–1087. https://doi.org/10.1089/tmj.2022.0161
  • Burau V, Falkenbach M, Neri S, Peckham S, Wallenburg I, Kuhlmann E (2022) Health system resilience and health workforce capacities: Comparing health system responses during the COVID‐19 pandemic in six European countries. The International Journal of Health Planning and Management 37(4): 2032–2048. https://doi.org/10.1002/hpm.3446
  • Carrillo de Albornoz S, Sia KL, Harris A (2022) The effectiveness of teleconsultations in primary care: systematic review. Family Practice 39(1): 168–182. https://doi.org/10.1093/fampra/cmab077
  • Cheng YY, Wang H, Liu LL, Zhang LP, Shen QF, Meng MF (2019) Application status and prospects of telemedicine in the field of burns. [Zhonghua Shao Shang za zhi = Zhonghua Shaoshang Zazhi =] Chinese Journal of Burns 35(9): 697–700.
  • Clark PA, Capuzzi K, Harrison J (2010) Telemedicine: medical, legal and ethical perspectives. Medical Science Monitor 16(12): RA261–72.
  • Cresswell K, Sheikh A (2013) Organizational issues in the implementation and adoption of health information technology innovations: an interpretative review. International Journal of Medical Informatics 82(5): e73–86. https://doi.org/10.1016/j.ijmedinf.2012.10.007
  • Cui F, Ma Q, He X, Zhai Y, Zhao J, Chen B, Sun D, Shi J, Cao M, Wang Z (2020) Implementation and application of telemedicine in China: cross-sectional study. JMIR mHealth and uHealth 8(10): e18426. https://doi.org/10.2196/18426
  • Demartines N, Freiermuth O, Mutter D, Heberer M, Harder F (2000) Knowledge and acceptance of telemedicine in surgery: a survey. Journal of Telemedicine and Telecare 6(3): 125–131. https://doi.org/10.1258/1357633001935167
  • Freiburger G, Holcomb M, Piper D (2007) The STARPAHC collection: part of an archive of the history of telemedicine. Journal of Telemedicine and Telecare 13(5): 221–223. https://doi.org/10.1258/135763307781458949
  • Ftouni R, AlJardali B, Hamdanieh M, Ftouni L, Salem N (2022) Challenges of telemedicine during the COVID-19 pandemic: a systematic review. BMC Medical Informatics and Decision Making 22(1): 207. https://doi.org/10.1186/s12911-022-01952-0
  • Funderskov KF, Boe Danbjørg D, Jess M, Munk L, Olsen Zwisler AD, Dieperink KB (2019) Telemedicine in specialised palliative care: Healthcare professionals’ and their perspectives on video consultations—A qualitative study. Journal of Clinical Nursing 28(21–22): 3966–3976. https://doi.org/10.1111/jocn.15004
  • Furlepa K, Tenderenda A, Kozłowski R, Marczak M, Wierzba W, Śliwczyński A (2022) Recommendations for the development of telemedicine in Poland based on the analysis of barriers and selected telemedicine solutions. International Journal of Environmental Research and Public Health 19(3): 1221. https://doi.org/10.3390/ijerph19031221
  • Hajesmaeel-Gohari S, Bahaadinbeigy K (2021) The most used questionnaires for evaluating telemedicine services. BMC Medical Informatics and Decision Making 21(1): 1–1. https://doi.org/10.1186/s12911-021-01407-y
  • Hassan A, Ghafoor M, Tariq SA, Zia T, Ahmad W (2019) High efficiency video coding (HEVC)–based surgical telementoring system using shallow convolutional neural network. Journal of Digital Imaging 32: 1027–1043. https://doi.org/10.1007/s10278-019-00206-2
  • Holtz BE (2021) Patients perceptions of telemedicine visits before and after the coronavirus disease 2019 pandemic. Telemedicine and e-Health 27(1): 107–112. https://doi.org/10.1089/tmj.2020.0168
  • Lokkerbol J, Adema D, Cuijpers P, Reynolds III CF, Schulz R, Weehuizen R, Smit F (2014) Improving the cost-effectiveness of a healthcare system for depressive disorders by implementing telemedicine: a health economic modeling study. The American Journal of Geriatric Psychiatry 22(3): 253–262. https://doi.org/10.1016/j.jagp.2013.01.058
  • Lopez AM, Lam K, Thota R (2021) Barriers and facilitators to telemedicine: can you hear me now? American Society of Clinical Oncology Educational Book 41: 25–36. https://doi.org/10.1200/EDBK_320827
  • Meher SK, Tyagi RS, Chaudhry T (2009) Awareness and attitudes to telemedicine among doctors and patients in India. Journal of Telemedicine and Telecare 15(3): 139–141. https://doi.org/10.1258/jtt.2009.003011
  • Nittari G, Khuman R, Baldoni S, Pallotta G, Battineni G, Sirignano A, Amenta F, Ricci G (2020) Telemedicine practice: review of the current ethical and legal challenges. Telemedicine and e-Health 26(12): 1427–1437. https://doi.org/10.1089/tmj.2019.0158
  • Peltan ID, Poll JB, Guidry D, Brown SM, Beninati W (2020) Acceptability and perceived utility of telemedical consultation during cardiac arrest resuscitation. a multicenter survey. Annals of the American Thoracic Society 17(3): 321–328. https://doi.org/10.1513/AnnalsATS.201906-485OC
  • Sarhan F (2009) Telemedicine in healthcare. 1: Exploring its uses, benefits and disadvantages. Nursing Times 105(42): 10–13.
  • Sharifi Kia A, Rafizadeh M, Shahmoradi L (2023) Telemedicine in the emergency department: an overview of systematic reviews. Journal of Public Health 31(8): 1193–1207. https://doi.org/10.1007/s10389-021-01684-x
  • Tjiptoatmadja NN, Alfian SD (2022) Knowledge, perception, and willingness to use telepharmacy among the general population in Indonesia. Frontiers in Public Health 10: 825554. https://doi.org/10.3389/fpubh.2022.825554
  • Wang G, Zhang Z, Feng Y, Sun L, Xiao X, Wang G, Gao Y, Wang H, Zhang H, Deng Y, Sun C (2017) Telemedicine in the management of type 2 diabetes mellitus. The American Journal of the Medical Sciences 353(1): 1–5. https://doi.org/10.1016/j.amjms.2016.10.008
  • Wilhite JA, Altshuler L, Fisher H, Gillespie C, Hanley K, Goldberg E, Wallach A, Zabar S (2022) The telemedicine takeover: Lessons learned during an emerging pandemic. Telemedicine and e-Health 28(3): 353–361. https://doi.org/10.1089/tmj.2021.0035
  • Zhai YK, Zhu WJ, Cai YL, Sun DX, Zhao J (2014) Clinical-and cost-effectiveness of telemedicine in type 2 diabetes mellitus: a systematic review and meta-analysis. Medicine 93(28). https://doi.org/10.1097/MD.0000000000000312
  • Zheng Y, Lin Y, Cui Y (2018) Teledermatology in China: history, current status, and the next step. InJournal of Investigative Dermatology Symposium Proceedings 19(2): S71–S73. https://doi.org/10.1016/j.jisp.2018.09.003

Supplementary material

Supplementary material 1 

Questionnaire and validation

Iman Hamdan, Enas Alkhader

Data type: docx

This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited.
Download file (34.60 kb)
login to comment