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The Survey of Willingness and Use of Information and Communication Technologies by People with Low Back Pain

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Abstract

Introduction:

Regular physical activity is effective in the treatment of low back pain. However, adherence to these exercises is difficult. Nowadays, the health care industry is using various forms of ICT to provide services to patients. Therefore, the aim of this study was to survey the willingness and use of information and communication technologies among people with low back pain.

Material and Methods:

This is an analytical study conducted in 2017. In this study, 200 samples low back pain were collected by use of convenience sampling method. The data collection tool was a checklist.

Results:

Nighty-nine percent of the participants used mobile phones based on Android; in addition, 51% of people stated that they were familiar with the Internet. Also, people with the mean age and standard deviation of 37 ± 9 were willing to use ICT tools more compared with people with the mean age and standard deviation of 45±13; in addition, they had a high willingness to use ICT tools and low willingness to use traditional tools (p<0.001).

Conclusion:

In general, the results showed that a large number of people with low back pain were willing to use ICT tools to receive care services (like exercise therapy). The majority of people with low back pain used social networks and they had smart phones based on the Android whose services were used widely. So the technologies such as smartphones, laptops, social networks and internet services could be used for e-learning.

INTRODUCTION

Low back pain (LBP) is the most common musculoskeletal disorder; also, it ranks among the top three leading causes of disability all over the world [1]. People with low back pain who do exercise at moderate to high levels have better progress in pain intensity, disability, and quality of life than people who do not exercise [2, 3]. However, ongoing adherence to this behavioral style is difficult. The use of Information and Communication Technologies (ICT) to do physical activity has dramatically increased. It seems that ICT can increases access and adherence to health care interventions [4].

ICT encompasses all digital technologies to exchange, collect, monitor and electronically store health information. It can provide chronic conditions management and health promotion [5, 6]. Each of the ICT tools such as computers, smartphones, applications based on the smartphone and tablet, social networks based on the smartphone, SMS, social media, internet services (web sites, Email) can support patients in the health care filed [7, 9]. Results of a study have shown that the provision of a rehabilitation program over the internet has improved the health condition of patients with chronic pain; also, more than half patients increased their work capacity [10]. Results of another study also shown that access to information through websites leads to a decreases in pain intensity, increase in physical activity; reduction in medical consultation, and the use of painkiller in patients with low pain [11].

Considering the fact that, nowadays, technologies such as the Internet, Social media and Applications are providing significant opportunities to improve the patients’ access to health care and also their clinical outcomes [11, 12]. Generally, through these technologies we can deliver therapeutic exercises to patients with low back pain remotely. Thus, before implementation of every tele-exercise therapy program, it is necessary to investigate the willingness of people with low back pain to use them. Given the fact that so far no study has been done on the Iranian population about this context, the main aim of this study is to survey the willingness and use of ICT among people with low back pain.

MARTIAL AND METHODS

This is an analytical study conducted in 2017 at Shiraz University of Medical Science. The study population consisted of people that suffer low back pain for more than three months who were referred to the rehabilitation center affiliated to Shiraz University of Medical Sciences (6 centers) . The sample size was calculated 178, but for the potential loss in the study, the sample size was considered 200. By referring to these clinics to access the samples during 2 months every day except holidays. Also, to collect the samples, we used the convenience sampling method. The data collection was a checklist that was made by researcher. The check list design steps included: 1) drawing flowcharts to analyze the aim of this study at three sections; 2) creating question bank through the available scientific literature; 3) selecting the best questions using expert opinion; 4) reviewing the check list by five experts in this field to determine the degree of agreement between them for validity of questions; 5) Redistributing the checklist among experts after revisions; 6) using the checklist as data gathering tool in this study. For the checklist to be filled correctly, the researchers provided adequate information to the patients. This checklist consisted of 3 parts: demographic information, the use of communication technologies on people with low back, and people's willingness to use ICT tools and traditional tools to receive care services. In the last part of this checklist, the willingness of people was scored base on the 5-degree Likert scale from 1(Not willing) to 5(high willingness). According to the number of questions in each section, a number was considered as the mid value of the possible score that subject can attain, so if the average score was more than the mid vale, the willingness of people to the type of tools to receive care services (ICT or traditional) was high. If that score was less than the Midvale the willingness of people to use the type of tool was low.

After completing the checklist, the data were processed by SPSS, version 21, software and descriptive and analytical statistics were used for their analysis. One sample t-test test were used to compare the mean of that the willingness of people to use ICT tools and traditional tools with mid value; the significance level was considered α= 0.05.

Results

Demographic data are shown in Table 1. The results showed that 85% of people had a history of back pain for more than 3 months. Also, the participants mentioned that having not enough time and commuting difficulty are the most important factors for failure to follow up their treatment courses (part 3 of check list).

Table 1

Demographic information

Variables (Mean ±SD)/ n (%)
Age(years) (42±12)
BMI(kg/m2) (25±4.03)
Gender (N=200) Female 133(67)
Male 67(33)
Marital status Single 47(24)
Married 153(76)
Level of education Collegiate 85(43)
Non Collegiate 114(57)
Job Health care worker 8(4)
Teacher 25(13)
Worker 26(14%)
Employed in the government 43(24)
Housewife 73(38)
Other 14(7)
Area of residence Urban 145(73)
Township 45(22)
Rural 10(5)

The results related to the use of communication technologies by people with low back pain showed that smart phones had the highest usage (58%) than any other communication technologies. 99% of the participants used smart phones based on Android; in addition, 51% of people stated that they were familiar with the Internet and they used the Internet whenever they needed (Table2).

Table 2

Using rate of information communication technologies by people with low back pain

Variables n(%)
More used technologies Personal computer 8))17
Lap top 6))12
Tablet device (2) 4
Smart phone 59))117
None of them 25))50
Type of cell-phone Simple phone 62(31)
Smart phone 138(69)
Type of Operation System of your cell-phone Android 136(99)
IOS 2(1)
Mobile Phone Services Message and conversation 165(82)
Application 112(56)
Internet 110(55)
Film 51(25)
Game 23(11)
Just conversation and I cannot use none of service 22(11)
just message 2(1)
Internet access Yes 162(82)
No 35(18)
Internet access via: Mobile phone 118(89)
Laptop 37(28)
Personal computer 37(28)
Tablet device 16(12)
Internet services Social networks 120(90)
Website 55(41)
Email 50(37)
None of them 3(1)
social networks installed on mobile phone, tablet, PC Telegram 104(84)
WhatsApp 95(75)
Instagram 41(32)
Viber 17(13)
Facebook 14(11)
LinkedIn 3(2)
More used Social Networks Telegram 66(53)
WhatsApp 51(41)
Instagram 6(4)
Viber 2(1)
Facebook 1(0)
Familiarity with the video communication program Imo 42 (21)
Skype 30(15)
Oovo 3(1)
Hangouts 3(1)
None of them 4(2)
The level of familiarity with the Internet I am familiar with the Internet, Also i know how to use it and I use it frequently 46(28)
I am familiar with the Internet, Also i know how to use of it and I use of it in the essential situation 83(51)
I am only familiar with the Internet, I do not know how to use of it, but my is frequently used of it 29(18)
I'm not familiar with the Internet, and my family do not use of it 4(3)
Time spent on the mobile Internet Less than an hour a week 19(15)
2 to 4 hours per week 40(34)
5 to 7 hours per week 26(20)
8 to 10 hours per week 10(8)
More than 10 hours per week 29(23)
laptop or computer internet Time spent on Less than an hour a week 22(32)
2 to 4 hours per week 22(32)
5 to 7 hours per week 12(18)
8 to 10 hours per week 3(4)
More than 10 hours per week 9(14)
Time spent on social networks 1 to 2hours 89(70)
3 to 5 hours 22(17)
5 to 7 hours 9(7)
More than 7 hours 6(4)

The results of one sample test showed that the willingness of people to use ICT tools was more than mid value score .therefore, they had a high willingness to use ICT tools (p<0.001). On the other hand, the willingness of people to use traditional tools was lower than mid value score. So, they had a low willingness to use traditional tools (p<0.001) (Table 3).

Table 3

Score of people willingness to use ICT tools and traditional tools

variables Number of questions per section Total score of each section Mean score for each section (mean±SD) p-value
ICT tools 4 20 (13±4) <0.001
Traditional tools 2 10 (5±2) <0.001

*p-values were results from one sample t-test

DISCUSSION

As the results revealed, people had high willingness to use ICI tools and they had a low willingness to use traditional tools to receive care services (like exercise therapy). This result may be due to two reasons: first, nowadays people use various types of information and communication technologies widely and second, since people do not have enough time to go to the clinic to exercise. So they have high willingness to use ICT tools. These results are consistent with those of Piechna et al., [13] in 2011 who investigated willingness people with musculoskeletal disorder to attend home-based exercises supervised over the internet. Their results indicated that people with low back pain had high willingness to use tele-rehabilitation and home-based exercise on the internet significantly. In addition, our results are in line with those of the Pew Internet & American Life Project and the California Health Care Foundation; these reports indicated that 49% of people who had more than one chronic disease used the Internet to do exercise. Also, more than half of these patients used various forms of internet services to improve their condition [14].

These technologies such as smartphones, laptops, social networks and internet services can be used for e-learning. This findings in our study was not compatible with the result of Parker et al., [15], which was done to identify the barriers and facilitators to older adults’ use of m-Health for pain management. In their study, they showed that the majority of older people tended to use m-health technology to manage their pain.

The results showed that 69% of people using smartphone and the majority of people (99%) had smartphones based on Android; moreover, the majority (82%) had access to the Internet and 51% of them were familiar with the Internet and its use whenever they needed. also, the majority of people (89%) had access to the Internet via mobile phone. This result may be due to the fact that the majority of people use the smartphone nowadays. It also seems that the majority of Iranian society use smartphones based on Android; moreover, the majority of the participants were residents of urban areas covered by internet broadband, so we think that people can have access to the internet. The results of our study are compatible with those of the Pew Internet & American Life Project and the California Health Care Foundation published in 2016, showing that the average of internet users in the developing countries was 45% in 2013. This figure increased to 54% in 2015. Twenty-one percent of people in developing countries had Smartphone in 2013; this rate reached 37% in 2015. Also, 76% of people across the world use the internet [16]. Also, the results of our study were compatible with those of Pearson et al., [17]; in their study, they showed that 83% of people with knee chronic pain used the Internet.

This study showed that the vast majority of people (90%) use social networks based on the internet; also, a lot of people use the Telegram and WhatsApp; in addition, our results showed that 71% of people used social networks 1 to 2 hours daily. It is a fact that nowadays people all over the world use social networks based on the tablets and smartphones largely [11]. Generally, it seems because social networks such as Telegram and WhatsApp are popular among the Iranian community; therefore, more participants use this social network. These results are in line with the findings of the reports of the Pew Internet & American Life Project and the California Health Care Foundation [18]. According to the data collected by the institute from 2005 to 2015, 65% of adults use social networks sites 10 times more than the past decade. Also, according to a research carried out in 2016 [19], WhatsApp was the second most popular social network from the list that is used by the Internet users. These results are in line with ours so that the users use more WhatsApp after the telegram.

CONCLUSION

In general, the results showed that people had a high willingness to use ICT tools and low willingness to use traditional tools. The majority of people with low back pain used social network and they had smart phones based on the Android whose services are used widely. In addition, half of the people are familiar with the internet. Hence, according to the results of this study, we suggest that applications design based on the android can be valuable to provide exercise to treatment patient with low back pain. Considering the fact that nowadays online social networks based tablet and smartphone have played an important role in our communication across the world and has been widely used all over the world. Accordingly, we think that the combination of smartphone and social networks services is an effective way for implementation of tele-exercise therapy programs to for people with low back pain.

Finally, we suggest that age is an effective factor in the willingness of people to use the e-learning to do exercise. Therefore, it seems necessary to increase the older people's willingness to use technology. We need to teach them how to use technology and design technologies such as applications easy enough to be used by the users.

ACKNOWLEDGEMENTS

The present article was adopted from Miss Niknam MSc. thesis in Health Information Technology, Faculty of Management and Medical Information Sciences, Health Human Resource Center, Shiraz University of Medical Sciences, Shiraz, Iran. The authors would like to thank the Research Vice-Chancellor of Shiraz University of Medical Sciences for financially supporting the research (Contract No. 95-01-07-11418). They also wish to thank the Research Consultation Center (RCC) for their invaluable assistance in editing this article.

LIMITATION

The lack of research in this field on the Iranian community that can be used to compared with our study in discussion and limited setting of the study are some of the limitations which should be considered in future studies.

AUTHOR’S CONTRIBUTION

Study development and design: Fatemeh Niknam, Omid Pournik and Roxana Sharifian. Data analysis and data collection: Fatemeh Niknam and, Naghmeh Ebrahimi. Paper preparation: Fatemeh Niknam, Omid Pournik, Zahra Rojhani, Naghmeh Ebrahimi,Roxana Sharifian. All the authors approved the final version of the manuscript.

CONFLICTS OF INTEREST

The authors declare no conflicts of interest regarding the publication of this study.

FINANCIAL DISCLOSURE

This study has been financially supported by Shiraz University of Medical Sciences (Contract No. 95-01-07-11418).

References

1. Buchbinder R, Blyth FM, March LM, Brooks P, Woolf AD, Hoy DG. Placing the global burden of low back pain in context. Best Pract Res Clin Rheumatol 2013;27(5):591–600. [PubMed] [Google Scholar] [CrossRef]
2. Pinto RZ, Ferreira PH, Kongsted A, Ferreira ML, Maher CG, Kent P. Self-reported moderate-to-vigorous leisure time physical activity predicts less pain and disability over 12 months in chronic and persistent low back pain. Eur J Pain 2014;18(4):1190–8. [PubMed] [Google Scholar] [CrossRef]
3. Vuori IM. Dose-response of physical activity and low back pain, osteoarthritis, and osteoporosis. Med Sci Sports Exerc 2001;33(6): S551–86. [PubMed] [Google Scholar] [CrossRef]
4. Bravata DM, Smith-Spangler C, Sundaram V, Gienger AL, Lin N, Lewis R, et al. Using pedometers to increase physical activity and improve health: A systematic review. Jama 2007;298(19):2296–304. [PubMed] [Google Scholar] [CrossRef]
5. Bashshur RL, Shannon GW, Krupinski EA, Grigsby J, Kvedar JC, Weinstein RS, et al. National telemedicine initiatives: Essential to healthcare reform. Telemed J E Health 2009;15(6):600–10. [PubMed] [Google Scholar] [CrossRef]
6. Gagnon MP, Desmartis M, Labrecque M, Car J, Pagliari C, Pluye P, et al. Systematic review of factors influencing the adoption of information and communication technologies by healthcare professionals. J Med Syst 2012;36(1):241–77. [PubMed] [PMC article] [Google Scholar] [CrossRef]
7. Levine M, Reid MC. Primary care providers’ perspectives on telemedicine in the pharmacologic management of older adults with chronic pain. Journal of the American Geriatrics Society 2012;60:S202.
8. Santoro E, Castelnuovo G, Zoppis I, Mauri G, Sicurello F. Social media and mobile applications in chronic disease prevention and management. Front Psychol 2015;6:567–70. [PubMed] [PMC article] [Google Scholar] [CrossRef]
9. Brattberg G. Internet-based rehabilitation for individuals with chronic pain and burnout: A randomized trial. Int J Rehabil Res 2006;29(3):221–7. [PubMed] [Google Scholar] [CrossRef]
10. Lee Ventola C. Social media and health care professionals: Benefits, risks, and best practices. P T 2014;39(7):491–9. [PubMed] [PMC article] [Google Scholar]
11. Schulz PJ, Rubinell S, Hartung U. An internet-based approach to enhance self-management of chronic low back pain in the Italian-speaking population of Switzerland: Results from a pilot study. Int J Public Health 2007;52(5):286–94. [PubMed] [Google Scholar] [CrossRef]
12. Krawczak K, Cabaj D, Kostrabala A, Piechna T, Chorzewsha A, Glinkowska B, et al. Willingness to attend home based exercises supervised over the Internet. The International confernce on eHealth Telemedicine and Health ICT Forum for Educational, Networking and Business 2011;:652–655.
13. Azizpoor Y, Hemmati F, Sayehmiri K. Prevalence of life-time back pain in Iran: a systematic review and meta-analysis. Scientific Journal of Kurdistan University of Medical Sciences 2013;18(4):102–12.
14.
citation-type="Government"
15. Parker SJ, Jessel S, Richardson JE, Reid MC. Older adults are mobile too! Identifying the barriers and facilitators to older adults’ use of mHealth for pain management. BMC Geriatr 2013;13:43–51. [PubMed] [PMC article] [Google Scholar] [CrossRef]
16.
citation-type="Government"
17. Pearson J, Walsh N, Carter D, Koskela S, Hurley M. Developing a web-based version of an exercise-based rehabilitation program for people with chronic knee and hip pain: A mixed methods study. JMIR Res Protoc 2016;5(2):e67. [PubMed] [PMC article] [Google Scholar] [CrossRef]
18.
citation-type="Government"
19.
citation-type="Government"

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