Assessing intention to use mobile phone–based self-management support among adults with type 2 diabetes in Saudi Arabia: A cross-sectional study

Abstract

Introduction

The use of mobile phone technology for chronic illness self-management is growing, and it may help people with type 2 diabetes mellitus (T2DM). Innovative methods are needed to improve patient involvement and disease management in the Kingdom of Saudi Arabia due to the high incidence of T2DM.

Objective

The purpose of this study was to explore how the T2DM patients in KSA utilizes their mobile phones for self-management.

Methods

A cross-sectional study was conducted between April and June 2024 among T2DM patients who were attending endocrinologists for their diabetes management in the Northern Border region (Rafha and Arar) and the Central region (Riyadh) in KSA using a validated questionnaire.

Results

This study included a total of 267 participants with T2DM. Nearly all participants (99.3%) possess a cellphone, with 94.8% having daily internet access. The majority of the patients reported to have an intention to use mobile phones and the internet for managing diabetes, with 78.3% for dietary planning, 79.4% for physical activity planning, and 78.7% for text messages as reminders. Factors such as female (p = 0.008), younger age (p = 0.001), and duration of diabetes (p = <0.001) were significantly associated with the intention to use mobile apps for managing their diabetes.

Conclusions

This study demonstrates a significantly higher inclination of participants toward mobile phone technology for diabetes self-management vs. face-to-face consultations. These findings highlight the promising role of mobile phone technology for enhancing diabetes self-management among T2DM patients, thus highlighting the need for targeted interventions.

Keywords

Type 2 diabetes mellitus smartphone internet self-management Saudi Arabia

Introduction

Worldwide, type 2 diabetes mellitus (T2DM) has reached epidemic proportions,¹ currently affecting 10.5% of the adult population.² At present, 374 million adults are living with prediabetes, which is projected to affect nearly 540 million adults by the year 2045.³ The rising prevalence of T2DM is attributed to factors such as aging,⁴ rapid urbanization,⁵ obesogenic environments,⁶ sedentary lifestyles,⁷ and genetic predisposition.⁸ According to the global burden of disease findings, diabetes mellitus (DM) was the eighth leading cause of death worldwide⁹; a total of 6.7 million deaths were attributed to DM in 2021 alone.¹⁰ According to various research findings, T2DM is associated with numerous complications, such as cardiovascular disease, cerebrovascular and peripheral vascular issues, nephropathy, retinopathy, amputations, diabetic foot, and depression.^11–13

In the Middle East, nearly 46 million individuals are affected by T2DM, with concerning patterns and trends in the overall prevalence, ranging from 2.6% to 21.9% over the past two decades.¹⁴ As of 2021, statistics from the International Diabetes Federation show that diabetes prevalence among adults was 25.5% in Kuwait,¹⁵ 17.7% in KSA,¹⁶ and 12.3% in the United Arab Emirates.¹⁷ A recent meta-analysis reporting the prevalence of T2DM in the general population of KSA reported a 16.4% pooled prevalence of T2DM.¹⁸ Developed nations have witnessed a rising trend in the prevalence of T2DM.¹⁹ The increased prevalence may be attributed to the higher prevalence of obesity among adults and higher risk factors for other non-communicable diseases²⁰; this is particularly evident in KSA, which ranks second in this regard.

Diabetes is a multifaceted condition, the management of which requires various daily self-management decisions by the patient.²¹ Similarly, diabetic patients need to possess knowledge and skills to understand their medical care requirements. Hence, T2DM self-management behavior is a crucial step required by diabetic patients in achieving better disease control and preventing disease-associated complications.^22,23 A recently conducted study also reported the importance of diabetes self-care management, which can effectively prevent and mitigate diabetes-related complications.²⁴ Owing to the high prevalence of DM as well as the importance of self-management behavior, practical, and affordable self-management programs are highly recommended for T2DM patients to improve health outcomes.²⁵ Since smartphones have become a vital part of many people's daily lives around the world, they are now being used as innovative healthcare tools for patients with DM.²⁶ Digital solutions, such as applications (“apps”) on smartphones, are increasingly in use in healthcare in general and for diabetes care in particular.^27–29 Numerous apps for managing DM have been developed; few of them can provide Bluetooth-enabled wireless data transfer to the smartphone from the measuring equipment.³⁰ Smartphone apps on diabetes management and self-management are available for the public to download from major app stores, including Google Play and Apple Store.^31,32 The majority of diabetic applications assist users in monitoring their blood sugar, nutrition, exercise, and prescriptions, which facilitates long-term health monitoring.^33–35 Studies reported a reduction in HbA1c level by using mobile apps for self-care and management of their DM.^36,37 Smartphone apps make it easy for patients to monitor and control their blood sugar by providing helpful information, reminders, and personalized tips.³⁸ Studies have shown that mobile phone interventions and mobile-based applications among diabetic patients can improve adherence to therapy and prevent disease complications.^39,40 Even due to advancements in technology, barriers to using health applications on smartphones include setting up an account, logging in, keeping track of usernames and passwords (which often require frequent changes for security), navigating the interface, and redownloading the application on new devices. There are concerns over the privacy and security risks endemic to the electronic storage and transmission of personal health information or that digital health will replace in-person communication.^41,42 KSA leads the Gulf region in smartphone, internet, and social media use,⁴³ with smartphone users forecasted to rise to 29.24 million by 2029⁴⁴ and mobile internet users growing to 39.18 million in the same period.⁴⁴

The number of smartphone apps for self-managing chronic diseases, particularly DM, is on the rise. However, unlike in advanced nations, such as the United States of America and Europe, there is a scarcity of studies in KSA exploring T2DM patients’ attitudes toward utilizing mobile phone applications for self-management of T2DM. Integrating technology, particularly smartphones, has the potential to significantly enhance diabetes care, especially in scenarios with limited access to primary healthcare or when patients face obstacles like time constraints, financial limitations, or geographical isolation.⁴⁵ Smartphones and internet connectivity offer avenues for expanding diabetes education and support services, particularly when patients encounter difficulties attending education sessions or consulting with diabetes educators regularly. Thus, this study aimed to investigate mobile phone usage among T2DM patients in Saudi Arabia and their willingness to employ such devices for self-management of T2DM.

Methods

Study design

A cross-sectional study was conducted between April and June 2024 and involved T2DM patients receiving diabetes management from endocrinology clinics. Given the regional variations in T2DM prevalence across KSA, as indicated in a meta-analysis,¹⁸ the chosen data collection sites encompassed diverse geographic areas, including the Northern Border region (Rafha and Arar) and the Central region (Riyadh). This selection includes both urban and rural areas, thereby ensuring a representative sample of the diverse population of KSA.

Inclusion criteria

The study's inclusion criteria included individuals who were 18 years of age or older, had completed at least a primary school education, had been diagnosed with diabetes by a qualified specialist, were proficient in using smartphones, and were native Arabic speakers. The exclusion criteria were those under the age of 18, people with type 1 diabetes, people who did not understand Arabic, and anyone who did not want to take part in the study.

Data collection sites

We collected data from various endocrinology clinics located in both urban and rural areas of Saudi Arabia's Northern Border region (Rafha and Arar) and Central region (Riyadh). The choice of these sites was made to show how people in different parts of KSA use and feel about mobile apps for managing T2DM, as was shown in a previous study that looked at differences in the number of people with T2DM in different areas.¹⁸

Data collection procedures and tools

Written informed consent was obtained from patients who were willing to participate after clearly explaining the objective of the study. Recruitment was carried out in endocrinology clinics in urban and rural areas in the selected locations. The participants were approached personally and were provided with a detailed explanation of the study's objectives and procedure. Written informed consent was obtained from individuals who agreed to participate and were requested to complete the paper-based questionnaire. The study did not provide any incentives or reimbursement to the patients for their participation.

For this study, a validated questionnaire²² consisting of 30 items divided into five sections was utilized. The questionnaire comprised 5 items related to demographic details, 5 items related to disease information, 6 items related to mobile phone and internet usage, 11 items for intention to use mobile phone apps for diabetes control, and 3 items for general explanations. Regarding mobile phone and internet usage, participants indicated whether they own a mobile phone, internet access, and their daily usage duration. The participants also gave details on their mobile phone activities. The section on attitude and intention for using mobile phones and Internet for diabetes management explored the services that the participants deemed necessary. The utilization of smartphones and apps for diabetes management was evaluated by using a five-point Likert scale, which ranged from “very bad” to “very good” across seven dimensions: idea feasibility, enjoyment, ease, excitement, interest, helpfulness, and cost-effectiveness. The smartphone apps and future intentions were also assessed using a five-point Likert scale, ranging from “no intention” to “very high intention”.

Ethics approval

Ethics approval was obtained from the institutional review board (IRB) having IRB Log Number: 2rt-193 as an essential step in ensuring that the current research adheres to ethical guidelines and safeguards the rights of participants.

Sample size calculation

The sample size for this study was calculated using a widely utilized formula.⁴⁶ Based on the anticipated prevalence of T2DM in KSA, that is, 21.4%,⁴⁷ a sample size of 255 was calculated, while assuming 5% precision (d), 95% confidence interval, 1.96 Z-statistics, and 0.21 as anticipated prevalence (p). However, we included a total of 267 patients for more accurate results.

Statistical analysis

Data analysis was performed using the SPSS 22 version. For categorical variables, the data were presented in frequency and percentages for categorical variables, and in mean and standard deviation for continuous variables. The association between the attitude and intention score was performed by using an independent t-test and one-way analysis of variance where appropriate. The statistical significance was kept at p-value <0.05.

Results

The study approached a total of n = 350 participants, but only n = 267 patients (response rate of 76.28%) participated, with the majority being female (55.4%) and primarily belonging to the 31–50 year age group (54.7%). Most of the patients (75.7%) resided in urban areas, and over half (55.4%) had completed their undergraduate education. The participants’ employment status varied, with 38.6% full-time employed and 18% retired. Regarding diabetes duration, 31.8% of patients had been diagnosed for more than five years, and 67% reported no comorbid conditions as depicted in Table 1.

Table 1.

Demographic characteristics of patients (n = 268).

Variables		N	%
Gender	Female	148	55.4
Gender	Male	119	44.6
Age in years	18–30 years	69	25.8
	31–40 years	74	27.7
	41–50 years	72	27.0
	51–60 years	40	15.0
	61 years and above	12	4.5
Place of residence	Urban	202	75.7
Place of residence	Rural	65	24.3
Education status	Primary level	25	9.4
	Secondary level	68	25.5
	Undergraduate level	148	55.4
	Postgraduate and higher	26	9.7
Employment status	Unemployed	35	13.1
	Retired	48	18.0
	Working full time	103	38.6
	Working part time	40	15.0
	Housewife	41	15.4
Duration of diabetes	Less than 6 months	56	21.0
	6 months to 1 year	54	20.2
	1 year to 3 years	41	15.4
	3 years to 5 years	31	11.6
	More than 5 years	85	31.8
Comorbid condition	No	179	67.0
Comorbid condition	Yes	88	33.0

Table 2 shows the general findings about participants’ use of cell phones and the Internet and their intention to use them for controlling their diabetes. Nearly all participants possess a cell phone (99.3%) and a smartphone (98.5%), with 94.8% having daily internet access. The majority of the patients expressed their intention to use their cell phones and the internet for managing T2DM, with 78.3% planning their diets, 79.4% planning their physical activities, and 78.7% using text message reminders. Additionally, 76.8% of participants reported an intention to use their cell phones for glucose reading and tracking, 74.9% for interacting with diabetes clinicians, and 77.5% for connecting with other healthcare providers, such as nutritionists, as shown in Table 2 (the Appendix Table is attached for further thorough responses from the participants).

Table 2.

Patients responses for use of current technology and intention regarding use of mobile phones and internet.

Question		Yes	No	Don’t know
Current technology use	“Having a mobile phone”	265 (99.3)	2 (0.7)	-
	“Having a smartphone”	263 (98.5)	4 (1.5)	-
	“Having daily access to the internet”	253 (94.8)	14 (5.2)	-
Intention to use mobile phones and the internet for diabetes control	“Dietary planning”	209 (78.3)	26 (9.7)	32 (12.0)
	“Physical activity planning”	212 (79.4)	29 (10.9)	26 (9.7)
	“Using text messages as a reminder for diabetes self-management”	210 (78.7)	30 (11.2)	27 (10.1)
	“Glucose reading and tracking options”	205 (76.8)	29 (10.9)	33 (12.4)
	“Communication with other people with type 2 diabetes”	174 (65.2)	45 (16.9)	48 (18.0)
	“Communication with diabetes clinicians”	200 (74.9)	28 (10.5)	39 (14.6)
	“Connect with other healthcare providers, such as nutrition, patients, etc.”	207 (77.5)	29 (10.9)	31 (11.6)

Table 3 illustrates the daily duration of internet and smartphone usage. Most of the patients (40.1%) were spending over 3 h each day on both the internet and smartphones.

Table 3.

Time spent by patients on smartphones/cell phones and the internet daily.

Question	N%
On average, how many hours a day do you spend on the internet?
Less than 1 h	27	10.1
Between 1 and 2 h	38	14.2
Between 2 and 3 h	71	26.6
Over 3 h	107	40.1
Don’t know	24	9.0
How many hours a day do you spend on your smartphone or cell phone?
Less than 1 h	27	10.1
Between 1 and 2 h	38	14.2
Between 2 and 3 h	70	26.2
Over 3 h	107	40.1
Don’t know	25	9.4

Figure 1 presents the patients’ attitudes toward using apps for diabetes control and their intention to use such apps in the future. The mean attitude score of the patients was 4.188 ± 1.134, while the mean intention score for future app use for diabetes control was 4.303 ± 1.030.

Figure 1.

Attitude score and intention score of patients for app use to their diabetes control.

The comparison of patients' attitudes and intention scores for using mobile apps to their diabetes control with demographic characteristics is shown in Table 4. The findings revealed that females showed a higher intention score (mean ± SD: 4.452 ± 0.928), with a statistically significant score compared to males (p = 0.008). The attitude score was higher in patients aged 18–30 years (mean ± SD: 1.878 ± 1.302), while the intention score was higher in patients aged 31–40 years (mean ± SD: 4.473 ± 0.814). A statistically significant difference was observed in the attitude and intention scores among the patients of different ages (p = 0.036) and (p = 0.001), respectively, as shown in Table 4. The attitude and intention scores showed no statistically significant difference when compared to education status. However, the comparison of diabetes duration with attitude and intention scores revealed a statistically significant difference, with p-values of <0.001 for each. Patients with a diabetes duration of 3–5 years had a higher attitude score (mean ± SD: 3.129 ± 1.310), while those with a diabetes duration of <6 months had a higher intention score (mean ± SD: 4.589 ± 0.848), as shown in Table 4.

Table 4.

Comparison of attitude and intention score of patients for us of apps toward their diabetes control.

Variables		Attitude score	p-value	Intention score	p-value
Gender	Female	2.108 ± 1.320	0.083 ^a	4.452 ± 0.928	0.008^*a
Gender	Male	2.403 ± 1.439	0.083 ^a	4.117 ± 1.121	0.008^*a
Age in years	18–30 years	2.550 ± 1.398	0.036 ^b	4.318 ± 0.865	0.001^*b
	31–40 years	1.878 ± 1.302		4.473 ± 0.814
	41–50 years	2.152 ± 1.380		4.430 ± 1.045
	51–60 years	2.475 ± 1.413		3.925 ± 1.327
	61 years and above	2.416 ± 1.311		3.666 ± 1.435
Education status	Primary level	2.122 ± 1.332	0.962 ^b	4.000 ± 1.290	0.084 ^b
	Secondary level	2.294 ± 1.393		4.117 ± 1.240
	Undergraduate level	2.236 ± 1.396		4.425 ± 0.865
	Postgraduate and higher	2.230 ± 1.394		4.384 ± 0.941
Duration of diabetes	Less than 6 months	1.714 ± 1.171	<0.001^*b	4.589 ± 0.848	<0.001^*b
	6 months to 1 year	1.740 ± 1.184		4.574 ± 0.923
	1 year to 3 years	2.268 ± 1.466		4.536 ± 0.636
	3 years to 5 years	3.129 ± 1.310		3.967 ± 1.110
	More than 5 years	2.564 ± 1.375		3.952 ± 1.194

Independent t-test; ^bOne-way ANOVA was used; *Statistically significant having a p-value of <0.05.

Discussion

This study revealed that the majority of the patients had access to smartphones and daily internet, with many expressing an intention to use these tools for T2DM self-care, including diet planning and exercise, tracking glucose, and connecting with healthcare providers. The study found that the mean intention score was significantly higher among female patients compared to males. Patients aged 18–30 years had a higher attitude score, and those aged 31–40 years had a higher intention score. Similarly, patients with a diabetes duration of 3–5 years presented a higher attitude score, whereas those with a diabetes duration of less than 6 months had a higher intention score for using mobile apps for T2DM management.

Self-management of chronic diseases is essential for lowering healthcare costs and improving health outcomes.^48,49 In T2DM management, the active engagement of patients in their care through consistent self-management practices is a fundamental aspect of clinical treatment. This active participation of patients not only helps control the disease but also plays a critical role in preventing its complications.⁵⁰ Furthermore, studies have shown that self-management strategies significantly improve glycemic outcomes in diabetes patients.^51,52 Apps for mobile devices are frequently used to support diabetic self-management.^33,53 By encouraging healthy lifestyle modifications, these apps have demonstrated efficacy in boosting diabetic self-care.^54,55

According to our study findings, 94.8% of participants regularly access the internet, and 98.5% of these participants own a smartphone. Our study findings are consistent with another study performed in KSA that found 94% of diabetics have access to the internet via computers, tablets, and mobile phones.⁵⁶ Our findings align with those of another Iranian study, which found that most participants had access to a mobile phone and the internet.²² Out of 33.25 million people, 30.25 million (91%) use the internet, and 25 million (75%) are engaged on social media in KSA.⁵⁷ Our study revealed that most patients intended to use smartphone apps and the internet to manage their diabetes. The participants in our study expressed intentions to use these tools for dietary planning, scheduling physical activities, monitoring blood sugar levels, communicating with diabetes specialists, and engaging with other healthcare professionals, such as dietitians. The results of our study align with those of studies performed in Iran,²² KSA,⁵⁶ Canada,⁵⁸ the United Kingdom,⁵⁹ and the Netherlands.⁶⁰ Given the higher trend of internet and smartphone apps for diabetes self-care, younger patients are more inclined towards using these technologies for diabetes self-management.²² A study conducted in Canada reported a greater inclination of younger T2DM patients toward the internet and mobile applications for diabetes self-management.⁶¹ Similarly, another study in England found that younger patients were more interested in using the internet and mobile applications for managing diabetes.⁵⁸

Similarly, the growing use of the internet and smartphones for self-care and T2DM management has led to a surge in the use of smartphone apps that offer features such as dietary management, blood glucose monitoring, and physical activity tracking.⁶² Several studies have investigated the impact of these technologies on diabetes-related outcomes.^63–68 In our study, the mean attitude score for using mobile apps to control diabetes was 4.188 ± 1.134, and the mean attitude score for intending to use apps in the future to control diabetes was 4.303 ± 1.030. Our study findings are in line with the findings of another study, where the mean attitude score was 4.18 ± 0.68 and the mean intention score for future use was 4.34 ± 0.75.²²

Our study findings revealed a statistically significant difference in intention scores between genders. However, as reported by another study no significance was found between gender and attitudes regarding intention in utilizing smartphone apps.²² Our study findings indicated that the attitude score was higher among patients aged 18–30 years, while the intention score was higher among those aged 31–40 years. There was a statistically significant difference in both attitude and intention scores across different age groups. In contrast, other studies have reported that older participants are generally less inclined to use web-based technologies, including the internet and smartphones.^56,58 In our study younger populations’ greater preference for and engagement in online activities may contribute to their higher use of the internet and smartphones compared to older age groups. Furthermore, in line with the results of another study,⁵⁸ our study showed a statistically significant difference in attitude and intention to use mobile apps for diabetes control, in line with the results of another study.

In our study, we found no statistically significant relationship between education level and the attitude or intention to use mobile apps for diabetes control; in contrast, another study found that utilizing technology to treat diabetes is more likely to be related to higher levels of education.⁵⁶ Higher education may also be associated with greater confidence and more informed decision-making when using mHealth technology, according to other research.^69,70 The lack of published research on this topic prevented us from directly comparing our results with those of other studies.

In this study, we examined patients’ attitudes and intentions regarding the use of mobile apps for managing T2DM. These findings suggest a direction for future research to explore how health professionals can leverage this information to identify individuals who would benefit most from mobile apps and support. This study has several limitations. Firstly, the questionnaire used was originally validated in an Iranian population; however, it was not validated for the Saudi context and no further linguistic or cultural validation was performed in the Arabic context for the questionnaire in this study. Furthermore, pilot testing was not conducted to assess the questionnaire's appropriateness for the Saudi population, which could have strengthened its reliability. However, future research should focus on developing and validating a questionnaire specifically tailored for Saudi Arabia, ensuring cultural and contextual relevance. Additionally, the inclusion criterion requiring smartphone proficiency may introduce bias, limiting the findings’ generalizability. Insights from this study provide valuable guidance for designing and implementing mobile app-based interventions and mHealth solutions to foster T2DM self-management in Saudi Arabia. Future research could explore ways to include a broader range of participants and investigate how support networks can enhance digital tool effectiveness in chronic disease management. Lastly, potential sampling biases could be a potential limitation, as the study was conducted in specific endocrinology clinics, potentially introducing biases due to the exclusion of patients from other healthcare settings.

Conclusion

Our study findings indicate that nearly all participants with T2DM own a smartphone and have daily internet access. The majority of the participating patients use mobile apps for dietary and physical activity planning, and they intend to use them for glucose reading and tracking, as well as for connecting with other healthcare providers, such as nutritionists. Factors such as gender, age, and length of diabetes were significantly associated with their intention to use mobile apps for managing their diabetes in the future.

Footnotes

Acknowledgments

The authors would like to thank the Research Center at King Fahad Medical City, Riyadh R2, Second Health Cluster, for the valuable technical support provided for the manuscript.

Contributorship

Conceptualization: Hind M.AlOsaimi, Mohammed Kanan. Data curation: Mohammed Kanan, Mohammed AlOtaibi, Saba Alhejaili. Formal analysis: Bayader Alshammari, Aleya Khalaf, Ryoof Saleh, Hind M.AlOsaimi, Mohammed Kanan. Funding acquisition: Mohammed Kanan. Investigation: Futoon Jamal, Amnah AbuShahin, Bandar Alanazi, Raghad Alshanbari. Methodology: Hind M.AlOsaimi, Mohammed Kanan, Ashwag Alsubaie, Ghadi Alasmari, Rana S.Alshahrani. Project administration: Hind M.AlOsaimi, Mohammed Kanan. Writing—initial draft: Mohammed AlOtaibi, Saba Alhejaili, Bayader Alshammari, Aleya Khalaf, Amal Hajea, Ryoof Saleh, Futoon Jamal. Writing—review and editing: Hind M.AlOsaimi, Mohammed Kanan, Amnah AbuShahin, Bandar Alanazi, Raghad Alshanbari, Ashwag Alsubaie, Ghadi Alasmari, Rana S.Alshahrani. All authors gave final approval of the version to be submitted.

Declaration of conflicting interests

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

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Gurantor

Mohammed Kanan

ORCID iDs

Mohammed Kanan

Saba Alhejaili

Appendix

Your attitude to diabetes self-management with using the internet and smartphone application (n = 267).

	N	%
For me, using a specially developed smartphone application to assist with self-management would be
Very bad idea	5	1.9
Bad idea	10	3.7
Neither a bad nor a good idea	26	9.7
Good idea	86	32.2
Very good idea	140	52.4
For me, using a specially developed smartphone application to assist with self-management would be
Extremely unenjoyable	143	53.6
Unenjoyable	4	1.5
Neither unenjoyable nor enjoyable	33	12.4
Enjoyable	87	32.6
Vert enjoyable	0	0.0
For me, using a specially developed smartphone application to assist with self-management would be
Very frightening	7	2.6
Frightening	8	3.0
Neither frightening nor comforting	25	9.4
Comforting	81	30.3
Very comforting	146	54.7
For me, using a specially developed smartphone application to assist with self-management would be
Very boring	9	3.4
Boring	6	2.2
Neither boring nor exciting	42	15.7
Exciting	70	26.2
Very exciting	140	52.4
For me, using a specially developed smartphone application to assist with self-management would be
Very dull	18	6.7
Dull	3	1.1
Neither dull nor interesting	33	12.4
Interesting	69	25.8
Very interesting	144	53.9
For me, using a specially developed smartphone application to assist with self-management would be
Very unhelpful	18	6.7
Unhelpful	3	1.1
Neither unhelpful nor helpful	33	12.4
Helpful	69	25.8
Very helpful	144	53.9
For me, using a specially developed smartphone application to assist with self-management would be
Very time-consuming	12	4.5
Time-consuming	9	3.4
Neither time-consuming nor time-saving	29	10.9
Time-saving	85	31.8
Very time-saving	132	49.4
I feel ….% confident that I could use a smartphone application to help me with my diabetes.
0%−20%	23	8.6
21%–40%	27	10.1
41%–60%	44	16.5
61%–80%	62	23.2
81%–100%	111	41.6
If you were unable to use a smartphone, would you want a spouse/friend/family member to help you manage your diabetes with a smartphone?
No	41	15.4
Yes	226	84.6
I intend to use a smartphone application to help me with my diabetes management in the future.
Not at all	12	4.5
Very little	7	2.6
Somewhat	20	7.5
A little	77	28.8
Very much	151	56.6

References

Fan

. Epidemiology in diabetes mellitus and cardiovascular disease. Cardiovasc Endocrinol Metab 2017; 6: 8–16.

Atlas

. IDF diabetes atlas. Brussels: International Diabetes Federation, 2021, Vol. 2021.

Saeedi

Petersohn

Salpea

, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas. Diabetes Res Clin Pract 2019; 157: 107843.

Wang

Zhao

Wang

, et al. Age-related disparities in diabetes risk attributable to modifiable risk factor profiles in Chinese adults: a nationwide, population-based, cohort study. Lancet Healthy Longevity 2021; 2: e618–e628.

Basit

Fawwad

Qureshi

, et al. Prevalence of diabetes, pre-diabetes and associated risk factors: second National Diabetes Survey of Pakistan (NDSP), 2016–2017. BMJ Open 2018; 8: e020961.

Chatterjee

Khunti

Davies

. Type 2 diabetes. Lancet 2017; 389: 2239–2251.

Ding

Tanaka

, et al. Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention. Int J Med Sci 2014; 11: 1185–1200.

Ligthart

Hasbani

Ahmadizar

, et al. Genetic susceptibility, obesity and lifetime risk of type 2 diabetes: the ARIC study and Rotterdam Study. Diabetic Med 2021; 38: e14639.

Ong

Stafford

McLaughlin

, et al. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2023; 402: 203–234.

10.

Bai

Shi

, et al. The global burden of type 2 diabetes attributable to tobacco: a secondary analysis from the global burden of disease study 2019. Front Endocrinol (Lausanne) 2022; 13: 905367.

11.

Papatheodorou

Banach

Bekiari

, et al. Complications of diabetes 2017. Hindawi, 2018.

12.

Wei

Tian

Tang

, et al. The influence of different types of diabetes on vascular complications. J Diabetes Res 2022; 2022: 1–12.

13.

Liu

, et al. Diabetic vascular diseases: molecular mechanisms and therapeutic strategies. Signal Transduct Target Ther 2023; 8: 52.

14.

Farmanfarma

Ansari-Moghaddam

Zareban

, et al. Prevalence of type 2 diabetes in middle–east: systematic review& meta-analysis. Prim Care Diabetes 2020; 14: 297–304.

15.

International Diabetes Federation. Diabetes in Kuwait (2021), https://idf.org/our-network/regions-and-members/middle-east-and-north-africa/members/kuwait/ (2021).

16.

International Diabetes Federation. Diabetes in Saudi Arabia (2021), https://idf.org/our-network/regions-and-members/middle-east-and-north-africa/members/saudi-arabia/ (2021).

17.

International Diabetes Federation. Diabetes in United Arab Emirates (2021), https://idf.org/our-network/regions-and-members/middle-east-and-north-africa/members/united-arab-emirates/ (2021, accessed 25 October 2024).

18.

Jarrar

Abusalah

MAH

Albaker

, et al. Prevalence of type 2 diabetes mellitus in the general population of Saudi Arabia, 2000–2020: a systematic review and meta-analysis of observational studies. Saudi J Med Med Sci 2023; 11: 1–10.

19.

Wani

Alfawaz

Alnaami

, et al. Effects of a 12-month intensive lifestyle monitoring program in predominantly overweight/obese Arab adults with prediabetes. Nutrients 2020; 12: 464.

20.

Okati-Aliabad

Ansari-Moghaddam

Kargar

, et al. Prevalence of obesity and overweight among adults in the Middle East countries from 2000 to 2020: a systematic review and meta-analysis. J Obes 2022; 2022: 1–18.

21.

Powers

Bardsley

Cypress

, et al. Diabetes self-management education and support in adults with type 2 diabetes: a consensus report of the American Diabetes Association, the Association of Diabetes Care & Education Specialists, the Academy of Nutrition and Dietetics, the American Academy of Family Physicians, the American Academy of PAs, the American Association of Nurse Practitioners, and the American Pharmacists Association. J Am Pharm Assoc 2020; 60: e1–e18.

22.

Rangraz Jeddi

Nabovati

Hamidi

, et al. Mobile phone usage in patients with type II diabetes and their intention to use it for self-management: a cross-sectional study in Iran. BMC Med Inform Decis Mak 2020; 20: 1–8.

23.

Alsaidan

Thirunavukkarasu

Alhassan

, et al. Evaluation of self-management behaviors and its correlation with the metabolic syndrome among the type 2 diabetes mellitus patients of northern Saudi Arabia. J Clin Med 2024; 13: 118.

24.

Gupta

Lakshmi

PVM

Chakrapani

, et al. Understanding the diabetes self-care behaviour in rural areas: perspective of patients with type 2 diabetes mellitus and healthcare professionals. PLoS ONE 2024; 19: e0297132.

25.

Kurnia

Amatayakul

Karuncharernpanit

. Predictors of diabetes self-management among type 2 diabetics in Indonesia: application theory of the health promotion model. Int J Nurs Sci 2017; 4: 260–265.

26.

Kuo

M-C

Liou

C-F

Lin

J-H

, et al. Barriers to mobile personal health assistant in patients living with diabetes. Health Inform J 2024; 30: 14604582241291522.

27.

Grundy

Wang

Bero

. Challenges in assessing mobile health app quality: a systematic review of prevalent and innovative methods. Am J Prev Med 2016; 51: 1051–1059.

28.

Hood

Wilson

Corsica

, et al. What do we know about mobile applications for diabetes self-management? A review of reviews. J Behav Med 2016; 39: 981–994.

29.

Greenwood

Gee

Fatkin

, et al. A systematic review of reviews evaluating technology-enabled diabetes self-management education and support. J Diabetes Sci Technol 2017; 11: 1015–1027.

30.

Lee

Kim

. Evaluation of Mobile applications for patients with diabetes mellitus: a scoping review. Healthcare 2024; 12: 368.

31.

Larbi

Randine

Årsand

, et al. Methods and evaluation criteria for apps and digital interventions for diabetes self-management: systematic review. J Med Internet Res 2020; 22: e18480.

32.

Veazie

Winchell

Gilbert

, et al. Rapid evidence review of mobile applications for self-management of diabetes. J Gen Intern Med 2018; 33: 1167–1176.

33.

Arnhold

Quade

Kirch

. Mobile applications for diabetics: a systematic review and expert-based usability evaluation considering the special requirements of diabetes patients age 50 years or older. J Med Internet Res 2014; 16: e104.

34.

Shan

Sarkar

Martin

. Digital health technology and mobile devices for the management of diabetes mellitus: state of the art. Diabetologia 2019; 62: 877–887.

35.

Janatkhah

Tabari-Khomeiran

Asadi-Louyeh

, et al. Usability of a disease management mobile application as perceived by patients with diabetes. CIN Comput Inf Nurs 2019; 37: 413–419.

36.

Ryan

Holland

Stroulia

, et al. Improved A1C levels in type 1 diabetes with smartphone app use. Can J Diabetes 2017; 41: 33–40.

37.

Tack

Lancee

Heeren

, et al. Glucose control, disease burden, and educational gaps in people with type 1 diabetes: exploratory study of an integrated mobile diabetes app. JMIR Diabetes 2018; 3: e17.

38.

Young

Miyamoto

Dharmar

, et al. Nurse coaching and mobile health compared with usual care to improve diabetes self-efficacy for persons with type 2 diabetes: randomized controlled trial. JMIR Mhealth Uhealth 2020; 8: e16665.

39.

de Souza Ferreira

de Aguiar Franco

dos Santos Lara

, et al. The effectiveness of mobile application for monitoring diabetes mellitus and hypertension in the adult and elderly population: systematic review and meta-analysis. BMC Health Serv Res 2023; 23: 55.

40.

Hakami

Almutairi

Alanazi

, et al. Effect of mobile apps on medication adherence of Type 2 diabetes mellitus: a systematic review of recent studies. Cureus 2024.16(1):e51791.

41.

Anthony

Campos-Castillo

Lim

. Who isn’t using patient portals and why? Evidence and implications from a national sample of US adults. Health Aff 2018; 37: 1948–1954.

42.

Lyles

Allen

Poole

, et al. “I want to keep the personal relationship with my doctor”: understanding barriers to portal use among African Americans and Latinos. J Med Internet Res 2016; 18: e263.

43.

Alanzi

. Mhealth for diabetes self-management in the Kingdom of Saudi Arabia: barriers and solutions. J Multidiscip Healthc 2018: 11, 535–546.

44.

Statista. Number of mobile phone internet users in Saudi Arabia from 2019 to 2029 https://www.statista.com/statistics/558821/number-of-mobile-internet-user-in-saudi-arabia/ (2024, accessed 25 October 2024).

45.

Luo

White-Means

. Evaluating the potential use of smartphone apps for diabetes self-management in an underserved population: a qualitative approach. Int J Environ Res Public Health 2021; 18: 9886.

46.

Daniel

. Biostatistics: a foundation for analysis in the health sciences. Wiley, 1978.

47.

Alwadeai

Alhammad

. Prevalence of type 2 diabetes mellitus and related factors among the general adult population in Saudi Arabia between 2016–2022: a systematic review and meta-analysis of the cross-sectional studies. Medicine (Baltimore) 2023; 102: e34021.

48.

Grady

Gough

. Self-management: a comprehensive approach to management of chronic conditions. Am J Public Health 2014; 104: e25–e31.

49.

Bodenheimer

Lorig

Holman

, et al. Patient self-management of chronic disease in primary care. JAMA 2002; 288: 2469–2475.

50.

Jiang

. The role of self-efficacy enhancement in improving self-management behavior for type 2 diabetes mellitus patients. Diabetes Metab Syndr Obes 2024: 17, 3131–3138.

51.

Chai

Yao

, et al. The effect of diabetes self-management education on psychological status and blood glucose in newly diagnosed patients with diabetes type 2. Patient Educ Couns 2018; 101: 1427–1432.

52.

John A

Davis

Price

, et al. The value of self-monitoring of blood glucose: a review of recent evidence. J Diabetes Complications 2010; 24: 129–141.

53.

Chomutare

Fernandez-Luque

Årsand

, et al. Features of mobile diabetes applications: review of the literature and analysis of current applications compared against evidence-based guidelines. J Med Internet Res 2011; 13: e65.

54.

Represas-Carrera

Martinez-Ques

Claveria

. Effectiveness of mobile applications in diabetic patients’ healthy lifestyles: a review of systematic reviews. Prim Care Diabetes 2021; 15: 751–760.

55.

Liu

Xie

. Effectiveness of mobile app-assisted self-care interventions for improving patient outcomes in type 2 diabetes and/or hypertension: systematic review and meta-analysis of randomized controlled trials. JMIR Mhealth Uhealth 2020; 8: e15779.

56.

Althubyani

Tang

Thomas

, et al. Evaluating the use of web-based technologies for self-management among Arabic-speaking immigrants living with type 2 diabetes mellitus: a cross-sectional study in Saudi Arabia. Diabetology 2024; 5: 85–95.

57.

Alenazi

Jamal

Batais

. Identification of type 2 diabetes management mobile app features and engagement strategies: modified Delphi approach. JMIR Mhealth Uhealth 2020; 8: e17083.

58.

Dobson

Hall

. A pilot study examining patient attitudes and intentions to adopt assistive technologies into type 2 diabetes self-management. J Diabetes Sci Technol 2015; 9: 309–315.

59.

Conway

Campbell

Forbes

, et al. Mhealth applications for diabetes: user preference and implications for app development. Health Informatics J 2016; 22: 1111–1120.

60.

Hofstede

de Bie

van Wijngaarden

, et al. Knowledge, use and attitude toward eHealth among patients with chronic lung diseases. Int J Med Inf 2014; 83: 967–974.

61.

Humble

Tolley

Krukowski

, et al. Use of and interest in mobile health for diabetes self-care in vulnerable populations. J Telemed Telecare 2016; 22: 32–38.

62.

Garcia-Zapirain

de la Torre Diez

de Abajo B

, et al. Development, technical, and user evaluation of a web mobile application for self-control of diabetes. Telemed J E Health 2016; 22: 778–785.

63.

Garabedian

Ross-Degnan

Wharam

. Mobile phone and smartphone technologies for diabetes care and self-management. Curr Diab Rep 2015; 15: 1–9.

64.

Krishna

Boren

. Diabetes self-management care via cell phone: a systematic review. J Diabetes Sci Technol 2008; 2: 509–517.

65.

Liang

Wang

Yang

, et al. Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis. Diabetic Med 2011; 28: 455–463.

66.

Bults

van Leersum

Olthuis

TJJ

, et al. Mobile health apps for the control and self-management of type 2 diabetes mellitus: qualitative study on users’ acceptability and acceptance. JMIR Diabetes 2023; 8: e41076.

67.

Kwan

Ong

Choo

DYX

, et al. A mobile application to improve diabetes self-management using rapid prototyping: iterative co-design approach in Asian settings. Patient Prefer Adherence 2023: 8:e41076..

68.

Mehraeen

Mehrtak

Janfaza

, et al. Design and development of a mobile-based self-care application for patients with type 2 diabetes. J Diabetes Sci Technol 2022; 16: 1008–1015.

69.

Song

Cramer

McRoy

, et al. Information needs, seeking behaviors, and support among low-income expectant women. Women Health 2013; 53: 824–842.

70.

Jafari

Karimi Moonaghi

Ahmady

, et al. Investigating readiness to use internet and mobile services of diabetic patients of a middle-income country. PeerJ PrePrints 2015; 3: e1111v1112.