Health information seeking behaviour using mobile devices among people with diabetes: A comparison between Middle and high income country

Abstract

Objective

The internet has become a primary source of information for many individuals especially those with chronic diseases. This study aims to understand and compare the health seeking behaviour using mobile devices among individuals with diabetes and between a high (Singapore) and middle (Malaysia) income country.

Methods

A cross sectional survey was conducted among people with diabetes in Malaysia and Singapore. Participants attending the primary health clinic for the treatment of diabetes were approached to participate in this survey. Data on demographics, health status and beliefs to health were collected and compared.

Results

A total of 673 respondents were included in the study. Most of the respondents reported to have access to the Internet, with a high ownership of mobile phones (99.3%). However, only one in every three respondents sought information online. Younger individuals (≤50 years) and those with higher education more likely to seek information using mobile devices. Respondents in Singapore reported to be more likely to use mobile devices to monitor their health as compared to respondents in Malaysia. However, most respondents would seek health information from their healthcare professionals’ especially physicians.

Conclusion

There was limited differences in the health-seeking behaviour among the respondents from both countries, suggesting for a need to identify for more effective means of distribution of health related information.

Keywords

Type 2 diabetes health-seeking behaviour cross-sectional survey m-health

Introduction

Diabetes currently contributes to a large component of the global burden of disease¹ and is one of the fastest growing non-communicable disease to affect people worldwide, with an estimated 425 million individuals globally affected by diabetes.² In many individuals with diabetes, self-management has been shown to be an essential strategy to help in achieving treatment target. Information seeking is an important aspect to cope with the disease especially in people with type 2 diabetes.^3–7 In this study, health-information seeking behaviours is defined as the way’s individuals seek “health related information such as risk, illnesses and health-protective behaviours”.⁸

While studies have suggested that majority of individuals prefer to learn and understand their condition from doctors personally, this may not be always possible due to time and geographical constrains as well as limited access to the attending doctor.^9–12 The advent of the Internet has provided both patients and healthcare providers an alternative source of medical information.^13,14 Among the attraction of online health information seeking is anonymity, potential for interactivity and social support.¹⁵

A recent Pew research report found that almost one in every three adults in the United States search for medical related information online.¹⁶ Some of the most common information sought were related to management of chronic illnesses, such as diabetes and hypertension. This was similarly noted in a recent review by Kuske and colleagues, where the authors reported that there has been a shift in the information seeking behaviour among individuals over the past few years. This was most evident among the younger generation, which preferred to seek information online compared to the older generation.¹⁷ However, Rains in their analysis of the Health Information Trends Survey found that many individuals still prefer to use traditional media or seek advice from healthcare professionals as their primary source of health information.¹⁸

Limited studies exist to explain such inconsistent findings. Studies have suggested that these could be due to the impact of readily health information leading to information overload which can also be conflicting and confusing. This is further confounded by the expectation of patients being an active partner of their own health management as well as cultural differences which may exist.¹⁹ As such, the ability to find and understand relevant quality health information is crucial for patients to participate in medical decision making, especially with the ease of availability of health information online. However, to date, there are limited studies that have examined the health seeking behaviour from Asian countries. The aim of the current study was to understand and compare the health seeking behaviour using mobile devices among people with type 2 diabetes between a middle and high income country.

Methods

Procedure

This study was a retrospective analysis of results from a self-administered surveys conducted clinics in Malaysia and Singapore. Both studies aimed to investigate the online health seeking behaviour and diabetes self management practices in each country. These countries were chosen primarily because Malaysia is a middle income country with a GDP per capita of USD$29,000 in 2017 while Singapore is a high income country with a GDP per capita of USD$93,900 in 2017.²⁰

Participants

This study was conducted at the 5 primary care clinics in the district of Petaling, Selangor, Malaysia and serves a population of approximately 2 million individuals. In Singapore, participants were recruited from a clinic within a public hospital which serves individuals with chronic diseases. From December 2014 to February 2016, individuals aged 18 years and older with type 2 diabetes who sought care at these primary care clinics were approached by a nurse or research assistant and invited to participate in the study. All participants were given an explanation on the purpose of study and individuals who agreed to this study were asked to complete the paper based survey instrument which took approximately 10 minutes to complete and return to the nurse or physician at each individual clinic. All participants provided written informed consent prior to entering the study. The Monash University Human Research Ethics Committee exempted the study from a full review (CF16/2328-2016001168) while the Nanyang Technological University’s Institutional Review Board granted an expedited review (IRB-2014-09-13)

Questionnaire development

The questionnaire was developed and adopted based upon a literature review of previous studies that have examined the use of m-health for health literacy.^{14,17,21–23} The questionnaire covered domains including (1) socio-demographics, (2) online health seeking behaviour and, (3) diabetes self-management practice. Respondents were asked to rate their level of agreement on a 5-point Likert scale (strongly agree to strongly disagree) relating to statements on their health seeking behaviour. The instrument was pilot tested among 10 volunteers at both sites to ensure clarity and comprehension. The final instrument was subsequently adapted and translated into Malay language and Mandarin and back translated for before being used in the current study.¹⁴

Statistical analysis

Descriptive statistics were calculated and tested using χ² test for categorical variables. To account for the imbalance in the number of responses collected between sites, we used the generalised estimating equation (GEE) technique. Potentially significant variables from the univariate analyses were imputed into the multivariate models, and corrected using the quasi-likelihood independence model. All statistical tests were performed using IBM SPSS ver. 21.0 (Armonyx, NY), with a 2-sided statistical test at 0.05 significance level.

Results

Overall, a total of 673 respondents were included in the current study, with 512 from Malaysia and 161 from Singapore (Table 1). There was an almost equal number of males (56%) and females (44%) respondents in the study, and most were aged 41 years and above (85%). Participants from Singapore were slightly younger than Malaysia. Most respondents from both countries were married and had some form of education.

Table 1.

Characteristics of all participants in the current study.

Characteristics	Total	Malaysia,n (%)	Singaporen (%)
Age (years)^a
21–30	23	7 (1.4)	16 (9.9)
31–40	75	57 (11.1)	18 (11.2)
41–50	187	135 (26.4)	52 (32.3)
51–60	388	313 (61.1)	75 (46.6)
Gender
Male	376	286 (55.9)	90 (55.9)
Female	297	226 (44.1)	71 (44.1)
Marital status^a
Single	63	12 (2.3)	51 (31.7)
Married	560	458 (89.5)	102 (63.4)
Divorced	18	13 (2.5)	5 (3.1)
Widowed	32	29 (5.7)	3 (1.9)
Educational level^a
No education	45	42 (8.2)	3 (1.9)
Primary/secondary	488	406 (79.3)	82 (50.9)
Diploma	102	51 (10.0)	51 (31.7)
Bachelor or higher	36	13 (2.5)	23 (14.3)
Comorbidities
Hypercholesterolemia^a	251	251 (49.0)	0 (0)
Hypertension^a	386	300 (58.6)	86 (53.4)
Ownership of device
Mobile phone^a	383	313 (61.1)	70 (43.5)
Smartphone^a	324	218 (42.6)	106 (65.8)
Tablet computer^a	73	40 (7.8)	33 (20.5)
Laptop^a	324	218 (42.6)	106 (65.8)
Desktop computer^a	57	19 (3.7)	38 (23.6)

^aP < 0.05 based upon χ² test.

Internet access

Most of the survey respondents reported that they had frequently accessed the Internet. Only one-quarter of the respondents reported that they owned at least 1 or more desktops/laptops at home (n = 161/673; 23.9%). In comparison, almost all respondents reported that they owned either a mobile phone or smartphone (n = 668/673; 99.3%). There were no significant differences in mobile phone ownership between both countries, but more respondents in Singapore owned a computer compared to Malaysia (Odds ratio (OR): 4.90; 95% CI: 3.31–7.25, p < 0.01). We found that younger respondents (aged 50 and below) were more likely to own several devices compared to older respondents (OR:2.17; 95% CI: 1.30–3.64, p = 0.003). This trend was noted in both Malaysia and Singapore.

Use of technology for health

Nearly half of respondents from both Malaysia (n = 156/356; 43.8%) and Singapore (n = 72/160; 45.0%) reported that they sought health related information online on their mobile phones. However, only 14.7% of respondent actively use some mobile health related applications in their daily lives. Most respondents were reported that they were receptive to the idea of adopting and using any mobile health related application for either improving their health (n = 313/673, 46.5%) or monitoring their blood glucose levels (n = 316/673, 47.0%). Singaporean respondents were more receptive with the idea of using technology for health monitoring as compared with their Malaysian counterpart.

Regression analysis of respondents found that older individuals aged >50 years and those with lower levels of education (those without any form of graduate education) had lower odds of engaging in online health information-seeking behaviour (Appendix Tables 1 and 2) This trend was noted in both Malaysia (OR: 4.35; 2.56–7.69, p < 0.001) and Singapore (OR: 3.85; 1.69–8.33, p < 0.001), where we found that younger individuals were more likely to seek health-related information online using mobile phones compared to the older adults. Interestingly, individuals who had a degree or higher were more likely to seek health related information online in Malaysia (OR 8.25; 2.06 – 33.10) but not Singapore (Table 2).

Table 2.

Logistic regression on correlates of health information seeking behaviour between countries.

Characteristics	Malaysia		Singapore
Characteristics	Odds ratio (95% CI)	p-value	Odds ratio (95% CI)	p-value
Age (years)
<50 years	4.35 (2.56–7.69)	<0.001	3.85 (1.69–8.33)	<0.001
>50 years	Ref		Ref
Gender
Female	Ref		Ref
Male	1.16 (0.79–1.69)	0.48	0.83 (0.44–1.55)	0.58
Education
No formal education	Ref		Ref
Primary/Secondary	1.43 (0.66–3.09)	0.36	3.10 (0.15–62.33)	0.74
Diploma	3.26 (1.30–8.17)	0.01	10.76 (0.53–219.3)	0.12
Bachelor or higher	8.25 (2.06–33.10)	0.002	18.85 (0.85–417.1)	0.06
Marital status
Single	Ref		Ref
Married	0.61 (0.19–1.96)	0.83	0.73 (0.37–1.43)	0.92
Divorced	0.62 (0.12–3.22)	0.57	1.44 (0.22–9.37)	0.38
Widowed	0.53 (0.13–2.18)	0.88	0.14 (0.01–2.80)	0.20

Perception of using technology for health monitoring

In general, most respondents (n = 440/673; 65.4%) reported that they were unaware of mobile health devices such as smartwatches or Bluetooth enabled glucometers (Appendix Table 2). They were, however, supportive of the idea of using such devices for the monitoring and management of their health condition. In particular, respondents from Singapore were more receptive to the idea of using technology for data collection and recording compared to respondents from Malaysia.

Discussion

Health information is increasingly being disseminated through the Internet.^12,22–24 This network is a rich and versatile platform for information sharing and interaction among different people. However, results of our study suggest that the current cohort of adults (e.g., individuals above 50 years old) are not likely to benefit from this shift to an online delivery of healthcare related content especially when delivered using mobile phones. Among all respondents, only 14.7% had installed a mHealth app (Appendix Table 1). Our findings are consistent, albeit lower, with previous literature showing that on average one in every three individuals had used a mHealth app.^25,26 Taken together, our study suggests that there is considerable space and opportunities for mHealth to grow in this region.

Education has been consistently shown to be one of the major determinant of health-seeking behaviour.^21,27 Our findings concur with this and found that younger participants and those with higher level of education were more willing use mobile devices to seek for health related information online. This observation is in part expected since individuals with higher levels of education generally have a higher socioeconomic status and thus own a smartphone. As such, efforts should be focused towards improving older adults’ knowledge and comfort with using mobile phones to search for information using the Internet, especially health related information. We believe that increasing the digital literacy of older adults,²⁸ such as teaching them to use computers and mobile phones as well as increasing accessibility to the Internet should be a given priority to ensure that only reliable and relevant health information is accessed by the patients.

Most participants expressed optimism and had a positive attitude towards the potential of using telehealth for disease management, education as well as monitoring. Given the increasing use of smartphones in the region, there is potential ramifications for public health policies. We believe that telehealth could be expanded to a larger population who are receptive towards this technology. For example, an e-health or telemonitoring program could be initiated to manage patients with diabetes in a particular region, fully managed by a central office. This could potentially lead to better patient outcome and cost savings.²⁹

Our study also highlights that some sub-categories of population such as the younger individuals, and those who are confident of taking care of themselves may benefit from using mHealth apps to achieve better health behaviours, and making medical care decision making, in line with the concept of person-centred care. Indeed, mHealth is now increasingly being used as a targeted intervention for the management of diabetes and other related chronic diseases.^6,7,30,31 This study also suggests that when providing health related information online, the differences in cognitive preferences between age groups and countries should be taken into account. For example, when designing for health campaigns, a two-prong approach may be needed, such as using social media or other related forums to target the younger individuals while traditional print media may be a more effective means to reach out to older adults.

This is the first study that attempted to compare the health seeking behaviour using mobile health between two countries in South East Asia. However, this needs to be taken in the light of some of the study limitations. Firstly, the survey was collected via convenience sampling and thus may not reflect the actual demographic composition of both countries. This may partly explain the discrepancy in terms of respondents between both countries. While both Malaysia and Singapore are multi-cultural countries, differences still exist. We did not verify the actual use of Internet or mHealth apps among respondents, and there was no follow-up discussion. We also did not request on the types of health information (e.g. disease specific information, advice etc.) or where this information was sought from (e.g. Google, World Health Organisation website). The samples were also limited to participants with diabetes, and we did not deliberately include individuals with other chronic diseases such as hypertension or hyperlipidaemia. As such, the results of this study should be interpreted with caution as the results presented may not reflect the actual habits of using mobile phones to search for health information in both countries. We also did not include participants from the general population which did not seek for help from these health clinics, which may be less educated. Finally, due to the retrospective nature of this study, no sample size or power calculation was performed. As such, our study maybe underpowered to detect any differences that may exists between both countries. As such, future studies should include individual level comparison, comparing individuals with chronic illness and general population, using a larger dataset and across multiple countries if possible.

Conclusion

We found that the health seeking behaviour using mobile phones were relatively similar between both countries. Younger individuals and those with those who have higher education were more likely to use mHealth to accomplish various health related task. This may help inform future researchers as well as industrial players on how they could further target their services and products to promote its use in the future.

Supplemental Material

sj-pdf-1-dhj-10.1177_2055207620956457 - Supplemental material for Health information seeking behaviour using mobile devices among people with diabetes: A comparison between Middle and high income country

Supplemental material, sj-pdf-1-dhj-10.1177_2055207620956457 for Health information seeking behaviour using mobile devices among people with diabetes: A comparison between Middle and high income country by Jason WY Lee, Yin-Leng Theng and Shaun WH Lee in Digital Health

Footnotes

Author contribution

All authors named contributed significantly to the document. JWYL and SWHL designed the study and supervised the data collection and drafted the manuscript. YLT and SWHL obtained funding. All authors critically reviewed the manuscript and approved the current final version.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

The Monash University Human Research Ethics Committee exempted the study from a full review (CF16/2328-2016001168) and from Nanyang Technological University Institutional Review Board (IRB-2014-09-013).

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was funded in part by an unrestricted research grant from the Nanyang Technology University and the e-Science fund from the Ministry of Science, Technology and Innovation, Malaysia [03-02-10-SF0238 (MOSTI)].

Guarantor

The corresponding author is the guarantor of this article.

Peer review

David Ka-Ki Wong, University of Hong Kong and Claudette Pretorius, University College Dublin have reviewed this manuscript.

ORCID iD

Shaun WH Lee

Supplemental material

Supplemental material for this article is available online.

References

James

Abate

, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the global burden of disease study 2017. Lancet 2018; 392: 1789–1858.

Ogurtsova

da Rocha Fernandes

Huang

, et al. IDF diabetes atlas: global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract 2017; 128: 40–50.

Weymann

Dirmaier

von Wolff

, et al. Effectiveness of a web-based tailored interactive health communication application for patients with type 2 diabetes or chronic low back pain: randomized controlled trial. J Med Internet Res 2015; 17: e53.

Lee

Chan

CKY

Chua

, et al. Intervention for diabetes with education, advancement and support (IDEAS) study: protocol for a cluster randomised controlled trial. BMC Health Serv Res 2016; 16: 524.

Lee

SWH

Nasir

, et al. Diabetes telemonitoring reduces the risk of hypoglycaemia during Ramadan: a pilot randomized controlled study. Diabet Med 2015; 32: 1658–1661.

Lee

SWH

Ooi

Lai

YK.

Telemedicine for the management of glycemic control and clinical outcomes of type 1 diabetes mellitus: a systematic review and meta-analysis of randomized controlled studies. Front Pharmacol 2017; 8: 330.

Lee

SWH

Chan

CKY

Chua

, et al. Comparative effectiveness of telemedicine strategies on type 2 diabetes management: a systematic review and network meta-analysis. Sci Rep 2017; 7: 12680.

Jacobs

Amuta

Jeon

KC.

Health information seeking in the digital age: an analysis of health information seeking behavior among US adults. Cogent Social Sciences 2017; 3: 1–11.

Lee

Chan

CKY

Chua

, et al. Using telemedicine to support care for people with type 2 diabetes mellitus: a qualitative analysis of patients’ perspectives. BMJ Open 2019; 9: e026575.

10.

Lee

Chan

CKY

Chua

, et al. Telemonitoring and team-based management of glycemic control on people with type 2 diabetes: a cluster-randomized controlled trial. J Gen Intern Med 2020; 35: 87–94.

11.

Lee

Hoti

Hughes

, et al. Consumer use of “Dr google”: a survey on health Information-Seeking behaviors and navigational needs. J Med Internet Res 2015; 17: e288.

12.

Jamal

Khan

AlHumud

, et al. Association of online health information-seeking behavior and Self-Care activities among type 2 diabetic patients in Saudi Arabia. J Med Internet Res 2015; 17: e196.

13.

Fox S and Purcell K. Chronic disease and the Internet, https://www.pewresearch.org/internet/2010/03/24/chronic-disease-and-the-internet/ (2010, accessed 15 March 2020).

14.

Lee

Wong

Lee

SWH.

m-Health views and perception among Malaysian: findings from a survey among individuals living in Selangor. mHealth 2020; 6: 6–13.

15.

Cline

Haynes

KM.

Consumer health information seeking on the internet: the state of the art. Health Educ Res 2001; 16: 671–692.

16.

Fox S and Duggan M. Health online 2013, https://www.pewresearch.org/internet/2013/01/15/health-online-2013/ (2013, accessed 15 March 2020).

17.

Kuske

Schiereck

Grobosch

, et al. Diabetes-related information-seeking behaviour: a systematic review. Syst Rev 2017; 6: 212.

18.

Rains

SA.

Perceptions of traditional information sources and use of the world wide web to seek health information: findings from the health information national trends survey. J Health Commun 2007; 12: 667–680.

19.

Song

Omori

Kim

, et al. Trusting social media as a source of health information: online surveys comparing the United States, Korea, and Hong Kong. J Med Internet Res 2016; 18: e25-e.

20.

World Bank Country and Lending Groups, https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups (2019, accessed 15 March 2020).

21.

Lorence

Park

Study of education disparities and health information seeking behavior. Cyberpsychol Behav 2007; 10: 149–151.

22.

Meyfroidt

Aeyels

Van Audenhove

, et al. How do patients with uncontrolled diabetes in the Brussels-Capital region seek and use information sources for their diet? Prim Health Care Res Dev 2013; 14: 229–239.

23.

Robertson

Akhtar

Petrie

, et al. How do people with diabetes access information? Pract Diab Int 2005; 22: 207–210.

24.

Laugesen

Hassanein

Yuan

The impact of internet health information on patient compliance: a research model and an empirical study. J Med Internet Res 2015; 17: e143.

25.

Bhuyan

Chandak

, et al. Use of mobile health applications for health-seeking behavior among US adults. J Med Syst 2016; 40: 153.

26.

Krebs

Duncan

DT.

Health app use among US mobile phone owners: a national survey. JMIR mHealth Uhealth 2015; 3: e101.

27.

Knapp

Madden

Wang

, et al. Internet use and eHealth literacy of low-income parents whose children have special health care needs. J Med Internet Res 2011; 13: e75.

28.

Miller

Bell

RA.

Online health information seeking: the influence of age, information trustworthiness, and search challenges. J Aging Health 2012; 24: 525–541.

29.

Lee

SWH.

Is telemedicine cost effectiveness for diabetes management: a systematic review. Diabetes Technol Ther 2018; 20: 492–500.

30.

Chongmelaxme

Lee

Dhippayom

, et al. The effects of telemedicine on asthma control and patients' quality of life in adults: a systematic review and meta-analysis. J Allergy Clin Immunol Pract 2019; 7: 199–216.e11.

31.

Tay

Lee

SWH

Yong

, et al. A systematic review and meta-analysis of the efficacy of custom game based virtual rehabilitation in improving physical functioning of patients with acquired brain injury. Tad 2018; 30: 1–23.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.10 MB