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Abstract

Background: Diabetes apps have the potential to improve self-management among people with type 2 diabetes mellitus (T2DM) and thereby prevent complications. However, premature disengagement of diabetes apps hinders this potential. Objective: This study aimed to identify facilitators of and barriers to the continued use of apps among T2DM patients and to formulate recommendations to enhance patients’ adherence to diabetes apps. Design: Qualitative study that followed the Consolidated Criteria for Reporting. Qualitative Research (COREQ) guidelines. Methods: Semi-structured interviews were conducted among 15 T2DM patients who continued real-world use of a diabetes app over 1 month. Data were analyzed using conventional content analysis. Results: The results showed that patients were triggered to continue app use by internally directed facilitators (health concerns, need for knowledge, self-conscious emotions) and externally directed facilitators (change in medication, reminders from health professionals). However, app use declined among all participants due to user-specific barriers (increased knowledge and experience, therapeutic inertia, diabetes stigma) and app-specific barriers. Notably, different app-specific barriers were identified in different self-managers: for novice self-managers, the app provided inconsistent information; for competent self-managers, the app provided invalid information and service; and for expert self-managers, the app was no longer being intelligent and new. Conclusions: The success of diabetes app continuance cannot be achieved by diabetes apps alone; rather, diabetes patients, health professionals, medical organizations, regulators, and integration technologies need to be gathered. Consistent, relevant, and current information, timely and continual service, psychological support should be guaranteed.

Keywords

type 2 diabetes mobile apps continued use qualitative conventional content analysis

Introduction

China has the largest number of people with diabetes in the world (140 million),¹ and more than 90% have type 2 diabetes mellitus (T2DM).² Approximately one adult with T2DM dies from complications every 8 seconds, with significant health, social and economic consequences.² Less than half (39.7%) of T2DM patients achieve the adequate self-management in China.^3,4 Diabetes apps for mobile phones have emerged as an effective additional intervention for self-management of T2DM.^5–7

Diabetes patients’ continuous use behavior is a prerequisite for the effectiveness of diabetes apps.⁸ However, one study found that among patients who adopted a diabetes app, 76.4% of them abandoned it quickly.⁹ Consistently, in another study patients’ usage of diabetes apps decreased markedly over time.¹⁰ A large-scale survey reported that patients who discontinued use of a diabetes app after 1 month experienced poorer HbA1c improvement than those who used a diabetes app for 1 year.¹¹ Premature dropout and low retention rates of diabetes apps interfere with app-based continuing care, limiting the possibility of developing further collaboration models between nurses and diabetes apps. Therefore, strategies to promote diabetes patients’ continuous use of diabetes apps are urgently needed.

A clear understanding of the barriers to and facilitators of app usage is the key to achieving patients’ continuous use.¹² Existing studies mainly focused on exploring the barriers and facilitators of mobile health usage, with the findings mainly centered two aspects.^13,14 First, the results were around the user aspect, such as users’ skills of using apps,^15,16 previous positive or negative emotional experience of using apps, ¹⁷ the available time to use apps,¹³ met or unmet expectations of apps,¹³ user’ desire to use,¹⁸ users’ motivation to make a lifestyle change,¹⁹ and users’ trust on apps.²⁰ Second, the results were around the app aspect, such as personalized information,^21–24 use of reminders/alerts, ^21,25,26 use of icons and colors, ^27–29 the use of data sharing, the performance of functions^13,14 and the authenticity of apps.²⁰ Moreover, existing studies mainly explored the barriers or facilitators of app usage within a short-term clinical condition.¹² Petersen and Hempler recruited 14 users to test a diabetes app over 4 weeks to reveal barriers of diabetes app continuance.³⁰ Short-term clinical conditions are very different from real-world conditions.¹² Studies explaining rationales for continuing or stopping app use among patients with different duration of diabetes app usage is limited. Existing interventions were mainly around the app aspect.^31–34 Most studies were dedicated to providing recommendations on user-friendly interface or functions, suggesting apps provide a simple, clean, and intuitive interfaces²⁸ and suggesting apps use gamification elements (such as reward systems, social characters, contests, and leaderboards). ^13,35

Overall, evidence of barriers, facilitators and interventions were often from a general mobile health perspective, which could serve as a reference. However, barriers and facilitators specific to diabetes patients and interventions targeted to diabetes apps were still insufficient. Thus, this study recruited T2DM patients who had used a diabetes app for different duration in real-world conditions to address the following research questions:

1. What are the facilitators and barriers for T2DM patients to continue using diabetes apps?

2. What recommendations can be provided to improve patients’ continuous engagement with diabetes apps?

Methods

Overview

This study conducted qualitative descriptive research using semi-structured and face-to-face interviews, and followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines. The study was approved by The Human Research Ethics Committee in Clinical Research (approval No. 2021-zx-012). All patients provided written informed consent prior to enrollment in the study.

Recruitment

The participants were consecutively recruited by purposive sampling from the National Metabolic Management Center (MMC) in Wenzhou, Zhejiang Province. The MMC is a Chinese innovation project for the management of metabolic diseases and complications.³⁶ The MMC in Wenzhou, Zhejiang Province, was one of the first MMC centers established in China. It serves patients in Wenzhou and southeastern Zhejiang. To promote continuing care in T2DM patients, the MMC developed a diabetes self-management app called “MMC app”.³⁶ The single app (MMC app) was recommended to all patients with diabetes who presented for the first time at the MMC center, and patients voluntarily decided to use it or not.

A maximum variation sampling technique was adopted to ensure the selection of a wide variety of participants in terms of age, app usage duration, diabetes duration, and educational level. The interviewer attended the diabetes clinic (located within the MMC) as a volunteer from August 2022 to November 2022 and invited patients in-person who: (1) had been diagnosed with T2DM; (2) had the experience of using the MMC app for more than 1 month³⁷; (3) were aged over 18 years; and (4) had good communication ability to participate in the study voluntarily. No prior relationship existed between the interviewer and the participants. In the MMC, when T2DM patients arrived, the interviewer first revealed her dual identity as a volunteer and a researcher to patients. Then, the interviewer assisted T2DM patients with registration, measuring height and weight. Next, the interviewer explained the purpose and significance of the research and invited patients who met the inclusion criteria to participate. The final sample included 15 T2DM patients without any rejection, among whom the majority were men aged 20–65 years, and the duration of app usage ranged from 1 month to 3 years.

The interviewer (the first author) is a female master’s student with a vast interest in diabetes self-management. The interviewer has experience in diabetes care and has been systematically trained in descriptive qualitative research and conventional content analysis. The research team has two tutors to ensure the quality of interviews and data analysis. Tutor 1 has rich experience in qualitative research and was on the team as an expert in qualitative methods. Tutor 2 has rich experience in clinical nursing and was on the team as an expert in diabetes care.

General overview of the “MMC app”

The “MMC app” was developed and funded by the National Metabolic Management Center. It mainly consisted of several modules: record module (record blood glucose, record blood pressure), knowledge education module, diet module (food calories and recommended recipes), consultation module (able to consult online) and medication module (able to record medication and insulin type). In the knowledge education module, users received updated information (called tweets) in the form of articles, videos etc. There were usually no references or sources of information in these tweets. Patients could view historical data and trend graphs, set reminders for medication, and add custom notes. In addition, the MMC app was connected to an independent digital medical record system. The MMC app enabled sharing of data between patients and health care professionals.

Procedure

The interviews were conducted in a secluded room and were digitally audio-recorded with written consent from all participants. Example questions are shown in Textbox 1. The researchers wrote the details needed to dig deeper and asked supplementary questions when appropriate. Pilot tests of three patients were conducted. When there was no new information emerging, three more interviews were conducted to ensure the data was saturated. The face-to face interviews lasted an average of 113 minutes. Two repeat interviews were carried out and lasted an average of 47 minutes. Transcripts were not returned to participants for comments, as most outpatient patients have a long follow-up period. It is difficult for interviewers to meet participants again.

Textbox 1.

Interview guide and example questions.

Interview topic: Ice-breaker

Example questions:

1. What is it like to have diabetes?

2. How do you manage your diabetes?

Interview topic: General use

Example questions:

1. Tell me the story of how you got started with this diabetes app?

2. How often do you use your diabetes app?

3. What features do you use the most and least?

4. Has there been any change in your usage? What was the change? What happened?

Interview topic: Potential facilitators

Example questions:

1. What makes you continue to use the app?

2. What situation will trigger you to continue using the app?

Interview topic: Perceived barriers

Example questions:

1. Tell me the advantages and disadvantages of each feature in the app. Can you give me an example?

2. What do you expect from the app in terms of features and functions?

3. How do you deal with difficulties if the app cannot meet your needs?

4. During your usage, has there been any change in your perception barriers? And how is it developed?

Data analysis

All interviews were audio-recorded, transcribed verbatim by a web-based transcription service, and calibrated verbatim by the first author. Transcripts were analyzed inductively using conventional content analysis.³⁸

Conventional content analysis approach is a flexible, intuitive, interpretive method widely used to describe a phenomenon and explore key problems of app usage.^38,39 It is also described as an inductive technique³⁸ reflecting in data coding and theme generation. According to conventional content analysis,⁴⁰ manifest and latent concepts from interviews are coded, abstracted, and categorized from interviews.

The Nvivo software (version 12.0) was used for data analysis.^40,41 Two researchers (the first author and the corresponding author) immersed themselves in the transcripts, and coding was done in Nvivo. The researcher (the first author) approached the text by making memos in Nvivo of her first impressions, thoughts, and initial analysis. The primary codes were assigned to semantic units potentially related to the research objective after reading each transcript word by word and line by line. As this process continued, primary codes emerged that reflect more than one key thought. These came directly from the text and then became the initial coding scheme. During the coding process, Nvivo was used to identify semantic units and modify terms. A continuous adjustment of the hierarchical relationship of the codes was also performed. Similar primary codes were combined into one category. All the primary codes that were relevant to each other and had semantic similarity were placed alongside each other to form a higher abstraction level known as subcategories. The subcategories related to each other and formed the main categories. These emerging categories were used to organize and group into sub-themes and themes. Table 3 presents an example of the interview coding process and data classification.

Results

Overview

The detailed demographic information of the study participants is presented in Table 1 and Table 2. Totally, we identified two themes, four sub-themes, and 11 categories related to continued app use (Figure 1 and Table 4).

Table 1.

Detailed demographic information of the interviewees (n = 15).

Participant	Gender	Age (years)	Self-reported duration of app usage	Duration of diabetes	Complications	HbA1C in the latest 3 months (%)	Educational background
ID1	Male	38	2 years	28 months	No	6.9%	Senior high school
ID2	Male	27	6 months	6 months	No	5.5%	Junior high school
ID3	Male	52	3 months	4 months	No	10.3%	Senior high school
ID4	Female	23	1 month	1 month	No	-	Undergraduate
ID5	Male	50	3 months	3 years	No	6.8%	Senior high school
ID6	Male	35	3 months	3 months	No	-	Senior high school
ID7	Male	50	3 years	3 years	Yes	6.4%	Primary school
ID8	Male	26	3 months	4 months	No	-	Junior high school
ID9	Male	41	3 years	10 years	No	-	Junior high school
ID10	Male	21	6 months	6 months	No	11.2%	Undergraduate
ID11	Male	49	8 months	10 months	No	-	Senior high school
ID12	Male	37	1 year	3 years	Yes	6.1%	Junior high school
ID13	Female	31	2 years	2.5 years	No	7.5%	Senior high school
ID14	Male	45	1 year	2 years	No	-	Senior high school
ID15	Male	65	2 months	2 months	Yes	-	Primary school

Note: “-” means that the patient’s HbA1C had not been tested in the previous 3 months.

Figure 1.

Results for app use facilitators and barriers.

Table 2.

Detailed demographic information of the interviewees (n = 15).

Variable	Number (%)
Gender
Male	13(86.7%)
Female	2(13.3%)
Age	Median = 38 years old
18-29 years old	4 (26.7%)
30-50 years old	7 (46.7%)
>50 years old	4 (26.7%)
Duration of diabetes	Median = 6 months
1-5 months	5(33.3%)
6-12 months	2(13.3%)
>1 year	8(53.3%)
Self-reported duration of app usage	Median = 10 months
1-3 months	6(40.0%)
4-6 months	2(13.3%)
7-12 months	3(20%)
>1 year	4(26.7%)
Complications
No	12(80.0%)
Yes	3(20.0%)
HbA1C in the latest 3 months	Median = 6.9%
<=6%	1(6.7%)
6%–11%	6(40%)
>11%	1(6.7%)
Has not been tested	7(46.7%)
Educational background
Primary school	2(13.3%)
Junior high school	4(26.7%)
Senior high school	7(46.7%)
Undergraduate or above	2(13.3%)

Table 3.

An example of the interview coding process and data classification.

Semantic units	Primary code	Subcategory	Category	Sub-theme	Theme
-When I observed a higher or lower reading, I would record blood glucose on the app every day and record daily diet as well. This can give me a sense of security	Worried about the abnormal blood glucose reading	The blood glucose concern	Health concerns	Internally directed facilitators	Facilitators
-When my blood sugar levels become abnormal, I would reflect on my behavior and see if something is wrong. Careful recordings in the app could give me a clear and deeper understanding of my behaviors	Worried about the abnormal blood sugar levels
-I feel uncomfortable in my body and numb in my hands, so I the app to search for information	Worried about numbness in hands	The somatic symptom concern
-I feel my eyes are very sore, and always shed tears and are unable to open them. I have been reading relevant contents on the app these days	Worried about eyes

Table 4.

Summary of identified themes.

Themes	Sub-themes	Categories	Sub-categories	Example quotes
Facilitators	Internally directed facilitators	Health concerns	The blood glucose concern	When I observed a higher or lower reading, I would record blood glucose on the app every day and record daily diet as well. This can give me a sense of security. (ID 4)
			The somatic symptom concern	I feel my eyes are very sore, and always shed tears and are unable to open them. I have been reading relevant contents on the app these days. I wonder if I should go to the hospital tomorrow and the day after tomorrow. I worry about whether it is caused by diabetes. (ID 4)
		Need for knowledge	Need for diabetes diet knowledge	When I encounter something I don’t know, I will go to the app to search. Usually it is the food. (ID 1)
				The biggest problem is that I don’t know which kind of foods I can eat, such as types of noodles and fruits… (ID 2)
			Need for diabetes exercise knowledge	I am curious about the intensity of exercise that patients with diabetes can do, so I have been constantly retrieving this information on the APP recently……(ID 7)
		Self-conscious emotions	Emotion of shame	…...Because there are always leftovers at home. My son came back for dinner at 8 p.m. I have to eat those leftovers that he can’t finish. My wife always asked me to handle these leftovers, and I also thought I should as I did not want to waste the food, but I know it is against the principle of self-management. I feel guilty. After eating, I always open the app to record my blood sugar, to look at the knowledge of diabetes diet…...Em...Just want to make up for it psychologically through using the app…(ID 1)
			Emotion of guilt	We have no choice. My job is to drink. I certainly know drinking is risky for [someone with] type 2 diabetes, but I can’t avoid it. What I can do only is to measure my blood sugar and record it immediately. (ID 9)
	Externally directed facilitators	Changes in medication	Changes in dose of medication	When the dose of insulin or medication is adjusted, I will record every day, and I think the reading is the most important. It helps the doctor and me to determine whether this adjustment is appropriate. I don’t need to explain too much to the doctor. He [the doctor] can fully grasp my condition through the blood glucose recording. (ID 4)
			Changes in type of medication	Sometimes, for example, if the medication changes, I will record [my blood glucose]. I often change the medication as I’m easily allergic to drugs. I changed my drugs again this time, and I record the data intensively in these days as in this way, I can understand if the new drug is effective for me. (ID 6)
		Reminders from health professionals	Reminder to check blood glucose	I come to the hospital for a regular examination every 3 months. When the doctor reminds me that I need to pay attention to my blood glucose, I would record my blood glucose frequently for 3 months. I feel secure with these records inexplicably. (ID 15)
			Reminders for self-management behaviors	During face-to-face consultations, doctors usually care about my usual behavior. When I engage in unhealthy behaviors such as drinking, the doctor will remind me. It warned me. I will immediately start paying attention to my behavior and recording my daily habits, including what I eat, whether I exercise, whether I drink alcohol, and so on. (ID 11)
Barriers	App-specific barriers	Novice self-managers: App provided inconsistent information	Information inconsistency	The clinic doctor didn’t ask me to count how much I eat every day. He just told me to eat normally, which is contrary to the app. For certain foods, doctors say that I can eat the apple, but the app says not. I was really confused when I was a novice. So, I simply abandoned the information in the app. (ID 9)
				The Wenzhounese often eat noodles. Noodle shops can be seen everywhere in Wenzhou. However, there was no recommendation about noodles in the recipes. (ID 4)
		Competent self-managers: App provided invalid information and service	Information inconsistent with practice	There is no diet suitable for going out; only recipes that can only be prepared at home. (ID 5)
			“One-size-fits-all” content	The diabetes app only tells you the importance of exercise and diet, and does not offer specific recommendations, or only offers some general descriptions. The information does not fit my diabetes progression. (ID 2)
			Online consultation invalid	I asked the online doctor but no one replied. Once I sent [a message about] my problem in the morning and did not receive the answer until the afternoon. My current questions or problems have passed already. (ID 2)
		Expert self-managers: App was no longer being intelligent and new	Manually enter blood glucose readings	I really feel a bit troublesome after using it for a long time. Can’t it upload automatically? I don’t use it much anymore. I feel it’s troublesome. (ID 1)
			No pop-up screens	When (the patient clicks on the app interface) it will display the state when there is newly published articles, but I need to click in to read. Some other apps can pop up directly on your mobile phone interface, which is more convenient. (ID 14)
			Repeated information	I already know all [the information on the app]! The information above the diabetes app is always repetitive, and there is no new cutting-edge information for me, such as the latest drug. In other words, the app is no longer valuable and helpful to me. (ID 12)
	User-specific barriers	Increased knowledge and experience	Diabetes knowledge accumulated	I know everything about diabetes, and I don’t need to use app anymore…(ID 14)
			Diabetes self-management experience accumulated	Now I can figure out most of my problems without searching around the app. I have a hunch that I will gradually stop using it. (ID 7)
		Therapeutic inertia	Therapeutic inertia when blood glucose was stable	“Em...Since I was diagnosed diabetes, I have been straining my nerves and monitoring blood glucose every day. It made me very tired. Em...just like the feeling of fatigue...Thus I really want to relax. Once my blood glucose is stable, I really want to have fun.” (ID 13)
			Therapeutic inertia at festivals	“In the festival, everyone around you is immersed in food. You would feel like an alien if you took out your diabetes app and ate healthy. Indeed, festivals are times to indulge.” (ID 13)
		Diabetes stigma	Concealing diabetes from others	“I have experience and found that many people who do not know about diabetes still have bad comments on it. For example, some think you are bad because you have this disease, and some may even think that they would be diagnosed with diabetes if they make friends with me. Thus, I did not let them know and dropped the app” (ID 10)
			Avoiding emotional distress of others	When I tell somebody that I am suffering diabetes, they always show pitiful expressions on their face. I don’t want to be pitied by others; it makes me feel stressed in my daily work. (ID 13)

Facilitators

We described facilitators from users’ internal and external perspectives.

Internally directed facilitators

Health concerns

Health concerns included the blood glucose and the somatic symptom concern. Some participants took blood glucose readings as a proxy measure of good or bad behavior. If they got an abnormal blood glucose reading occasionally, they restarted, maintained, or increased their frequency of blood glucose recording, noting their behaviors every day in the app and trying to identify the bad ones.

“When my blood sugar levels become abnormal, I would reflect on my behavior and see if something is wrong. Careful recordings in the app could give me a clear and deeper understanding of my behaviors.” (ID 5)

Some participants were highly sensitive to somatic symptoms, including itchy skin, cough, numbness of hands, or uncomfortable eyes. These somatic symptoms concerned them that their diabetes might be progressing. They consulted online resources, retrieved somatic symptoms, or recorded notes of their symptoms in the app to guide their further health-seeking behavior.

“I’ve became very sensitive to the physical symptoms since my diagnosis [of diabetes]. When my eyes or hands feel uncomfortable, I worry about whether it is caused by diabetes and whether my disease is progressing. For this time, I use the app to control my diabetes progression.” (ID 13)

Need for knowledge

Need for knowledge stimulated participants to actively search for information in the app. Participants described how they had been learning about self-management since they were diagnosed. If they came across something beyond their knowledge, they would use the diabetes app to search for relevant information owing to its real-time availability. Similarly, behavior stimulation by the diet and exercise knowledge need became less frequent as participants became expert self-managers.

“Sometimes I desire to eat meat or noodles as I have eaten vegetables for too long, but I don't know which type of meat I can eat, so I will search on the app.” (ID 2)

Self-conscious emotions

Self-conscious emotions drove patients to continue using the diabetes app. Some participants declared that if they did something not aligned with the rules of diabetes self-management, they experienced the negative emotion of shame or guilt. These internal constructive emotions facilitated participants to use the diabetes app.

“.....As there are always leftovers at home. My wife always asked me to handle these leftovers and I also thought I should eat those leftovers. However, I am a diabetic and I know it is against the principle of self-management. I felt guilty every time when I overeating. At this point, I would open it [diabetes app] to look at recipes and make records. Em……just want to make up for it psychologically ...” (ID 1)

Drinking was an inevitable situation in Chinese social situations.⁴² Participants, especially young men, mentioned that drinking was necessary in their social interactions. Participants believed that they should take responsibility for their unhealthy behaviors and thus would search on the app for remedial actions.

“It is unavoidable. I have to drink with my client unless I do not want this job anymore. But afterwards, I use the app to search for what can be done to make up for it after drinking, so that I can be responsible for my own behavior.” (ID 12)

Externally directed facilitators

Changes in medication

Changes in prescribed medication (e.g., a change in the type or dose) would stimulate participants to record blood glucose levels and search for medication information in the app. Some participants viewed the records as a reliable assurance for professionals making medication decisions.

“When the doctor changed my medication, I would increase my usage of the app to record my blood glucose, almost every day for at least two weeks, because I wanted to keep track of my blood glucose fluctuations after changing the medication.” (ID 6)

Reminders from health professionals

Some participants regarded health professionals as authorities. Some participants described that health professionals always asked them about their self-management behaviors and gave them gentle persuasion or criticism for misbehaviors. Another group of participants expressed unconditional compliance with health professionals because they wanted to act as good patients.

“...What the doctor said is definitely correct. Every patient should follow the doctor. They ask me to learn more knowledge, so I learn it. I do whatever they tell me to do. I want to be a good patient.” (ID 14)

Barriers

We describe app- and user-specific barriers below.

App-specific barriers

Novice self-managers: app provided inconsistent information

Novice self-managers referred those patients who were new to diabetes management and were often newly diagnosed. Participants strongly described the information provided by the knowledge education module and diet module of the app. For novices, inconsistent information between the app and professionals was a hindrance to continued use. As participants were novice self-managers, the paucity of self-management experience made them eager for every piece of information in the app. They lacked the ability to judge information and relied primarily on the professionals. Many expressed that the inconsistency of the information had a paralyzing effect on their behaviors to continue using the app, and some even abandoned it.

“The doctor told me that I could eat noodles, but the app said noodles are not suitable for diabetic people, I was so confused.” (ID 1)

Competent self-managers: app provided invalid information and service

Competent self-managers referred those who had a basic understanding of diabetes and were beginning to apply theory to practice by relating the information obtained to its actual context. Participants mentioned the knowledge education module, diet module, and consultation module of the app, which provided information and services. Competent self-managers declared that they were no longer novices and gradually acquired self-management skills. For competent self-managers, the separation of information from practice, “one-size-fits-all” information content, and invalid online consultations were three significant barriers that prevented participants from becoming long-term app users.

Diet and exercise information provided by apps was separated from the practice. Participants described calorie-based recipes were not in line with Chinese dietary habits. Chinese dietary habits have high diversity of ingredients and combinations that make calorie calculations difficult. Moreover, different parts of China have different regional dishes, and recipes based on local foods were not available in the app. For exercise information, some participants were eager for more specific suggestions that could be easily integrated into their daily lives.

“To be honest, I think the recipes are impractical. I don't think we can accurately calculate calories at all. We can't eat in this way. Also the exercise suggestion.” (ID 3)

Some participants illustrated that they lost interest as they were not helped by the “one-size” content.

“Well...for example this article entitled “five kinds of fruits that diabetics can eat”. When I was new, I will read it, but currently, I know that everyone is unique. However, the content provided by the app is the same. This can only be used as a reference. It doesn’t really work for me”. (ID 14)

Some participants labeled online consultation as invalid due to the delayed response. Participants felt disappointed and they lost their desire to continue using the app. They mentioned that medical professionals on the app were unable to provide ongoing outpatient services, rendering their consultations invalid.

“I asked the online doctor but received no response. Once I asked the doctor on the app in the morning, and I did not receive the response until the afternoon. The problem had been solved by then.” (ID 2)

Expert self-managers: app was no longer intelligent and new

Expert self-managers referred those who were familiar with diabetes and were able to diagnose a situation and respond appropriately to it on an intuitive basis. The record module and knowledge education module of the app were criticized by participants. Expert self-managers declared that in this stage, they were familiar to diabetes and were able to diagnose a situation and respond appropriately to it on an intuitive basis. Some participants had become experts in diabetes self-management with a wealth of experience and knowledge. They perceived that manually inputting blood glucose readings and clicking within the app had become cumbersome, tiring, and annoying. They continued to use the app not only for primary needs (e.g., recording the readings, providing the information), but also for more intelligent functions (e.g., automatically uploading the readings, pop-up cards).

“I have been using the app for almost one year. To be honest, I already know everything about diabetes management. Now I just hope it [the app] can become more convenient. For example, information can pop up on its own.” (ID 14)

The repeated presentation of information and the absence of the latest diabetes advances were also shortcomings. Some participants chose to minimize their engagement due to the repeated information and the absence of the latest diabetes advances. Some participants declared that information in the app “had stopped updating for a month” (ID1). They lost interest in “go in (the app)” because they had got familiar with the repeated information. Some participants expressed that they abandoned the information because it did not meet their needs for the latest advances in diabetes clinical trials, including technology, medication, or treatments. Information that was not cutting-edge and repeated disappointed participants, .

“I have already known all [the information on the app]! The information above the diabetes app is always repetitive, and there is no new cutting-edge information for me. This app is no longer valuable and helpful to me.” (ID 12)

User-specific barriers

Increased knowledge and experience

Increased knowledge and experience are significant barriers to continuing app use. Participants’ experience accumulated with the use process. They became “experts” at self-management, knowing how to handle occasional lapses, understanding their physical signs and symptoms during episodes of hyperglycemia, and even adjusting the dose delivered by the insulin pen in a flexible way. They perceived a sense of mastery over self-management and felt it unnecessary to continue using the app.

“At the beginning, I was new to diabetes. Now I can say that I have already become half of a diabetes expert. As the saying goes, prolonged illness makes a doctor of a patient. I do not need the app anymore, as I can handle most of the problems by myself.” (ID 12)

Therapeutic inertia

Therapeutic inertia, refers to the failure to initiate or intensify therapy in a timely manner according to diabetes self-management guidelines.⁴³ Participants voiced that maintaining a high level of self-discipline for a long time can make people tired. When they found their blood glucose was stable, they would indulge their feeling of monitoring fatigue and have fun.

“Yes, I did stop using the app about one month ago as I was getting to the stable stage..... My blood glucose didn’t fluctuate up and down. It is a chance to relax.” (ID 15)

Important festivals in China also triggered their therapeutic inertia and their discontinuation of app use. Participants said they always lost normal control over diet and exercise, and temporarily quit using the app during the holidays. In part, participants explained it in terms of collectivism in Chinese culture. They described wanting to be part of the group, so they quit the diabetes app and took personalized action.

“Honestly, I can't eat this or that ... It is tough for me to control the diet for so long... I get fed up with it. The Chinese Spring Festival is coming soon. I desire to enjoy, to eat some dessert, and to have a drink with my brothers.” (ID10)

Diabetes stigma

Diabetes stigma was a salient barrier to continuing app use, especially for young adults. Some participants described that most people labeled negative stereotyping to T2DM, including “overweight”, “poor”, and “someone who injected insulin”. They felt “uncomfortable and ashamed” (ID4,10) of using the diabetes app in front of others. One participant (ID13), who changed her work environment, expressed she planned to stop using the app, as using the diabetes app exposed her diabetes. She did not want to receive sympathy, shock, worry, or even discrimination from others.

“When my friends or classmates knew I was diabetic, they said, ‘Oh you must inject insulin, it is horrible.’ I was uncomfortable when I heard it. Thus, now I try not to let them know and I do not use the diabetes app in front of them.” (ID 4)

“When I tell somebody that I am suffering from diabetes, they always show pitiful expressions on their face. I don't want to be pitied by others; it makes me feel stressed in my daily work.” (ID 13)

Discussion

Principal findings

This qualitative study obtained valuable insights from 15 T2DM patients who had continued using the MMC diabetes app for at least 1 month in a real-world setting. It suggests gathering patients, professionals, app designers, and organizations to facilitate internally and externally facilitators, play the role of health professionals, provide consistent, relevant, and current information, provide timely and continual service, and deliver psychological support.

Facilitate internally and externally directed facilitators

Consistent with previous studies,⁴⁴ self-conscious emotions (e.g., guilt or shame) have a motivating effect on people’s willingness to initiate a task. When T2DM patients experience inevitable setbacks during self-management strivings, self-conscious emotions are raised as a powerful internal resource, facilitating patients to continuously use the app. Emotional resilience training, designed to advance understanding and recognition of self-conscious emotions, could be recommended for medical organizations.⁴⁴ In addition, we found that diabetes apps were used by patients as a means of coping with overeating or drinking. Guidelines or standards from authoritative institutions (e.g., the American Diabetes Association (ADA)) are suggested to provide apps evidence-based remedial advice. For example, the 2023 Standards of Care in Diabetes suggested that people with diabetes should be educated about the risks of drinking (e.g., hypoglycemia, delayed hypoglycemia) and encouraged to monitor glucose frequently after drinking alcohol to minimize such risks.⁴⁵

Changing in prescribed medication (e.g., a change in type or dose) has a motivating effect on T2DM patients’ continuous use behavior. In line with previous studies,⁴⁶ patients’ treatment was associated with their daily self-care behaviors. When T2DM patients changed their treatment, they would frequently check their sugar and record it on the app. It suggests that diabetes apps have an organizational design to update changes in patients’ treatment. When patients changed the type or dose of prescribed medication, diabetes apps could remind patients of follow-up actions,⁴⁶ such as recording blood glucose levels and popping up medication information.

Appropriate role of health professionals

Our findings support those of previous studies that health professionals play a crucial role in advancing use of digital devices.⁴⁷ No diabetes management device works optimally without ongoing support by health professionals.⁴⁸ Moreover, with the accumulation of experience and stabilization of health conditions, patients were less triggered by internally directed facilitators. In line with previous studies,^49,50 T2DM patients were more internally motivated in the initial usage and sought more external support for long-term engagement. This further illustrates the limitations of diabetes apps in maintaining patient self-management behaviors, and that the need for ongoing education and support from health professionals cannot be ignored. When patients intended to reduce or drop usage of the app, we suggest that health professionals can support patients’ emotions, perceptions, reflections, and self-management behaviors, both online and offline, to enhance their continued use of the app.

Provide consistent, relevant, and current information

The finding of this study was in line with DeLone and McLean’s Model of Information Systems Success,⁵¹ which indicated that information quality, especially information consistency, could significantly influence users’ continuous use behavior. Ensuring the consistency of information between health professionals and diabetes apps could reduce any chance of confusion or mismanagement, and be particularly important for newly diagnosed patients.⁵² Obviously, this issue cannot be solved by the diabetes app alone; rather, diabetes patients, health professionals, app designers, and organizations need to be gathered.^47,53 Before starting to use the diabetes app, novices should first understand the principles of diabetes self-management and information judgment. It is suggested that medical organizations offer online or offline self-management training to patients who are initially recommended the diabetes app. Health professionals and expert self-managers are encouraged to be trainers. Moreover, the knowledge education module of the “MMC app” currently relies largely on articles and videos from unknown sources. Diabetes apps are recommended to provide authoritative and credible information. It could be done by quoting reputable diabetes specialists, referencing authoritative organizations, and providing credentials from healthcare professionals or organizations.

Our study confirmed previous findings^54,55 that long-term users expect the diabetes app to provide actionable information relevant to their lives, which often centered around diet and exercise. We suggest that diabetes apps utilize emerging technologies such as machine learning or motion detections, to automatically analyze individuals’ daily lifestyles and generate personalized recommendations for their daily behaviors. For example, for a patient who takes the bus from home to work every weekday morning, diabetes apps could pop up exercise suggestions at the right time that are personalized based on exercise type (i.e., walking), time (i.e., every weekday morning), location (i.e., routine from the home to the bus stop), and weather (i.e., sunny). Consistent with previous studies,^56,57 patients prefer feasible dietary suggestions that are consistent with Chinese dietary habits. Instead of measuring food intake in grams, milliliters, and calories, our findings suggest diabetes apps use serving sizes common in China in the descriptions of dietary recipes, such as household units of measurement (e.g., cup, tablespoon).

In accordance with prior research,^54,58 much empirical research identified experience as a barrier stopping people from continuing to use personal health apps. Patients achieving behavior change goals and thus losing the sense of benefit from health apps.⁵⁴ As described in results, patient demand for the latest advances might overwhelm app availability in the later stages of app usage. Patients weave their information web of diabetes self-management over time, and new information is constantly added to their network as they gain experience.⁵⁹ Diabetes apps could not provide the latest information, and as a result, patients used the app less frequently. We suggest that diabetes apps deliver cutting-edge information by regularly following up on the latest literature on T2DM, such as the latest treatments and reversal of T2DM, to keep patients engaged. Health professionals are encouraged to joint together to translating information into text, video, and images that are easy to understand, consistent, and fit patient’s routines and Chinese cultural norms.

Provide timely and continual service

In line with Information Systems Success,⁵¹ this study has verified the significance of service quality on T2DM patients’ continued use behavior of diabetes apps. Our study revealed the issue of delayed responses to online consultation, which was widely identified but not addressed.^60,61 Part of the reason for this dilemma is the shortage and high workload burden of Chinese health professionals.⁶² Other stakeholders in the diabetes community should work with and alongside health professionals in addressing this issue.⁶³ Diabetes apps could establish a medical consortium⁶⁴ among community health centers and hospitals to optimize online consultation. Employing competently trained health coaches tend to be another way to alleviate this problem.^65,66 Diabetes apps with one-to-one health coaches could provide patients with frequent, personalized and timely services. According to research,⁶⁶ certified human health coaches employed by digital health platform received education regarding the disease knowledge and were trained to interact with the digital health platform for data collection and communication. In coordination with the diabetes clinical team, health coaches would answer any questions, provide educational content, track patient-reported outcomes, and facilitate referrals and resources.⁶⁶ The burden of online consultations with health professionals will be greatly reduced. On the other hand, in an emergency, online consultation of diabetes apps might not be the best option for T2DM patients. The diabetes APP is more of an auxiliary than a replacement for offline consultation,⁴⁷ thus patients are suggested to seek offline medical advice immediately when they meet emergencies. Health professionals are recommended to educate patients about the pros and cons of diabetes apps and inform patients about the potential limitations of using diabetes apps.

T2DM patients valued online support provided by the same person over time. Previous studies highlighted the significance of personalized and ongoing online diabetes education after diagnosis.^67,68 However, they did not focus on the person who offered online diabetes support. Diabetes apps could schedule healthcare teams to be online at different times and publish detailed online schedules within the app, which has been attempted in China.⁶⁹ This could empower patients with the opportunity to choose the same person. Mitigating patients’ negative experiences with randomly assigned healthcare providers is an effective way to reduce patient attrition. Based on informed consent, our study suggests that diabetes apps should support data sharing between healthcare providers and patients, including patients’ self-recorded data within the app. Data sharing can eliminate the need for patients to repeatedly describe their problems to different healthcare providers and help healthcare providers quickly understand their concerns.

Provide psychological support

Diabetes stigma was one of the user-specific barriers. Our results indicated that younger adults with T2DM, including college students, fresh graduates, and workplace novices, were more likely to experience or be more sensitive to diabetes stigma. Supported by the most extant literature,^70,71 diabetes stigma tended to be age-related. In an international review, the prevalence of diabetes stigma has been reported as high as 98% in youth and adolescents⁷² This finding might be explained by young adults being more psychologically sensitive to peer pressure,⁷³ as they preoccupied with how their peers view them and want to fit in.^71,74 Consistent with prior studies,⁷⁵ experiencing diabetes stigma had behavioral consequences that disrupted patients’ continued app use. It suggests that diabetes apps should be designed not only to help with behavioral management but also to reduce the emotional burden of diabetes stigma.^75,76 Diabetes apps are suggested to integrate a peer support module for helping patients overcome the negative mindset associated with diabetes stigma.^9,77 However, depending merely on online peer support through an app is insufficient. Communities, hospitals, and other stakeholders should also create peer supporter groups to provide patients psychological intervention.⁷⁷ Health professionals also should pay close attention to young T2DM patients and guide them to establish a healthy understanding of diabetes.

Limitations and suggestions for future research

Here are several limitations that need to be clarified. This study involves mainly primarily young and middle-aged adults, so the implications for the elderly may be limited. It may be due to the fact that very few older adults use diabetes apps, and even fewer continue using.⁷⁸ A study revealed that only two out of 32 elderly diabetes patients had used a diabetes app.⁷⁹ It suggests that more future research is needed to understand the plight of elderly diabetics. Secondly, the predominance of males is another limitation, which can be explained by disease and digital health perspectives. In terms of diabetes epidemiology, male adults have a higher prevalence of diabetes. IDF Diabetes Atlas 2021 reported that the estimated prevalence of diabetes in men (10.8%) aged 20–79 years was higher than in women (10.2%).¹ In 2021, there were 17.7 million more men than women living with diabetes.¹ In terms of digital health studies, males are more likely than females to continue using digital health.^80,81 Health wearables wear time was found to be higher in males (78%) than females (66%).⁸² It may, however, affect the generalizability of the findings. Third, T2DM patients in this study were recruited from a hospital outpatient clinic. While we attempted to mitigate this limitation by deliberately sampling participants of different ages, future studies should target patients with a wider geographic distribution, particularly in communities and families. Fourth, our study employed T2DM patients who were living in China and some results appeared to be bound to Chinese culture (e.g., collectivist culture). It is possible to generalize the findings to other nations with similar cultures, especially those in East Asia.⁸³

Conclusions

This study revealed a range of facilitators and barriers related to diabetes app use and offered recommendations to encourage continued usage of diabetes apps. Diabetes apps integrate emerging technologies to provide information relevant to patients’ daily lives along with psychological support and information adapted to the knowledge level of users. Notably, relying on a diabetes app alone to maintain patient long-term engagement was not enough, diabetes patients, health professionals, medical organizations, regulators, and integration technologies need to be involved.

Supplemental Material

Supplemental Material - Diabetes apps cannot “stand alone”: A qualitative study of facilitators and barriers to the continued use of diabetes apps among type 2 diabetes

Supplemental Material for Diabetes apps cannot “stand alone”: A qualitative study of facilitators and barriers to the continued use of diabetes apps among type 2 diabetes by Yucong Shen, Jingyun Zheng, Lingling Lin, Liyuan Hu, Zhongqiu Lu, Chenchen Gao in Health Informatics Journal

Footnotes

Author contributions

Yucong Shen: Data curation, Statistical analysis, Writing-Original draft, Writing-Reviewing and editing.

Jingyun Zheng: Data curation.

Lingling Lin: Data curation.

Liyuan Hu: Data curation.

Zhongqiu Lu: Conceptualization, Supervision.

Chenchen Gao: Statistical analysis; Conceptualization, Supervision, Writing-Reviewing and editing.

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.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Key Laboratory of Geriatric Long-term Care (Naval Medical University), Ministry of Education (Grant Number: LNYBPY-2023-17), Zhejiang Office of Philosophy and Social Science (22NDQN253YB) and Natural science foundation of Zhejiang Province (LQ21G030017).

Joint first authorship

All authors approved the revised manuscript as submitted.

Contributorship

All authors approved the revised manuscript as submitted.

Ethical statement

ORCID iD

Yucong Shen

Supplemental Material

Supplemental material for this article is available online.

References

International Diabetes Federation . IDF diabetes Atlas. 10th ed., 2021. Brussels.

Chinese Diabetes Society . Guideline for the prevention and treatment of type 2 diabetes mellitus in China (2020 edition). Chinese Journal Diabetes Mellitus 2021; 13(4): 315–409.

Weng

Pozzilli

. Diabetes metabolism: research and reviews--Chinese diabetes society special issue: a small but encouraging step toward the successful control of diabetes in China. Diabetes Metab Res Rev 2014; 30(6): 445–456.

Tang

Luo

, et al. The role of family support in diabetes self-management among rural adult patients. J Clin Nurs 2023; 32(19-20): 7238–7246.

Hou

Carter

Hewitt

, et al. Do mobile phone applications improve glycemic control (HbA1c) in the self-management of diabetes? A systematic review, meta-analysis, and GRADE of 14 randomized trials. Diabetes Care 2016; 39(11): 2089–2095.

Istepanian

. Mobile applications for diabetes management: efficacy issues and regulatory challenges. Lancet Diabetes Endocrinol 2015; 3(12): 921–933.

Whitehead

Seaton

. The effectiveness of self-management mobile phone and tablet apps in long-term condition management: a systematic review. J Med Internet Res 2016; 18(5): e97.

Bhattacherjee

. Understanding information systems continuance: An expectation-confirmation model. MIS Q 2001; 25(3): 351–370.

Zhang

Luo

, et al. Exploration of users' perspectives and needs and design of a type 1 diabetes management mobile app: mixed-methods study. JMIR Mhealth Uhealth 2018; 6(9): e11400.

10.

Fisher

Fortmann

Florissi

, et al. How frequently and for how long do adults with type 2 diabetes use management apps? The reall study. J Diabetes Sci Technol 2021; 6: 19322968211058766.

11.

Y-Z

Chang

Y-T

Chiou

H-Y

, et al. The effects of continuous usage of a diabetes management app on glycemic control in real-world clinical practice: Retrospective analysis. J Med Internet Res 2021; 23(7): e23227.

12.

Katz

Dalton

Price

. Failing the challenge: diabetes apps & long-term daily adoption. In: 8th International Conference on Advanced Technologies & Treatments for Diabetes (ATTD 2015), 18-21 February 2015, Paris. 2015.

13.

Jakob

Harperink

Rudolf

, et al. Factors influencing adherence to mHealth apps for prevention or management of Non communicable diseases: systematic review. J Med Internet Res 2022; 24(5): e35371.

14.

Wilson

Heinsch

Betts

, et al. Barriers and facilitators to the use of e-health by older adults: a scoping review. BMC Publ Health 2021; 21: 1556–1612.

15.

Cajita

Hodgson

Lam

, et al. Facilitators of and barriers to mHealth adoption in older adults with heart failure. Comput Inform Nurs 2018; 36(8): 376–382.

16.

Zibrik

Khan

Bangar

, et al. Patient and community centered eHealth: exploring eHealth barriers and facilitators for chronic disease self-management within British Columbia’s immigrant Chinese and Punjabi seniors. Health Policy and Technology 2015; 4(4): 348–356.

17.

De Veer

Peeters

Brabers

, et al. Determinants of the intention to use e-Health by community dwelling older people. BMC Health Serv Res 2015; 15: 103–109.

18.

Mishuris

Stewart

Fix

, et al. Barriers to patient portal access among veterans receiving home‐based primary care: a qualitative study. Health Expect 2015; 18(6): 2296–2305.

19.

Bujnowska-Fedak

Pirogowicz

. Support for e-health services among elderly primary care patients. Telemed J e Health 2014; 20(8): 696–704.

20.

Pywell

Vijaykumar

Dodd

, et al. Barriers to older adults’ uptake of mobile-based mental health interventions. Digit Health 2020; 6: 2055207620905422.

21.

Laurens

Pieterse

Brusse-Keizer

, et al. Alcohol avoidance training as a mobile app for problem drinkers: Longitudinal feasibility study. JMIR Mhealth Uhealth 2020; 8(4): e16217.

22.

Zeng

Heffner

Copeland

, et al. Get with the program: adherence to a smartphone app for smoking cessation. Addict Behav 2016; 63: 120–124.

23.

Orlemann

Reljic

Zenker

, et al. A Novel mobile phone app (OncoFood) to record and optimize the dietary behavior of oncologic patients: Pilot study. JMIR Cancer 2018; 4(2): e10703.

24.

Chen

Wong

Ayob

, et al. Can Malaysian young adults report dietary intake using a food diary mobile application? A Pilot study on acceptability and compliance. Nutrients 2017; 9(1): 62.

25.

Bell

Garnett

Qian

, et al. Engagement with a behavior change app for alcohol reduction: data visualization for longitudinal observational study. J Med Internet Res 2020; 22(12): e23369.

26.

Park

K Shim

, et al. Perceptions and experiences of using mobile technology for medication adherence among older adults with coronary heart disease: a qualitative study. Digit Health 2020; 6: 2055207620926844.

27.

Deng

Chen

Liu

, et al. Using mobile health technology to deliver a community-based closed-loop management system for chronic obstructive pulmonary disease patients in remote areas of China: Development and prospective observational study. JMIR Mhealth Uhealth 2020; 8(11): e15978.

28.

Collins

DAJ

Harvey

Lavender

, et al. A Pilot evaluation of a smartphone application for workplace depression. Int J Environ Res Public Health 2020; 17(18): 6753.

29.

Aji

Glozier

Bartlett

, et al. A feasibility study of a mobile app to treat insomnia. Transl Behav Med 2021; 11(2): 604–612.

30.

Petersen

Hempler

. Development and testing of a mobile application to support diabetes self-management for people with newly diagnosed type 2 diabetes: a design thinking case study. BMC Med Inform Decis Mak 2017; 17(1): 91.

31.

Serrano

Coa

, et al. Characterizing user engagement with health app data: a data mining approach. Transl Behav Med 2017; 7(2): 277–285.

32.

Rahman

Janmohamed

Pirbaglou

, et al. Patterns of user engagement with the mobile app, manage My Pain: results of a data mining investigation. JMIR Mhealth Uhealth 2017; 5(7): e96.

33.

Becker

Kribben

Meister

, et al. User profiles of a smartphone application to support drug adherence--experiences from the iNephro project. PLoS One 2013; 8(10): e78547.

34.

Taki

Lymer

Russell

, et al. Assessing user engagement of an mHealth intervention: Development and implementation of the Growing healthy app engagement Index. JMIR Mhealth Uhealth 2017; 5(6): e89.

35.

Gong

Baptista

Russell

, et al. My diabetes Coach, a mobile app-based interactive conversational agent to support type 2 diabetes self-management: randomized effectiveness-implementation trial. J Med Internet Res 2020; 22(11): e20322.

36.

Zhang

Wang

Ning

. Metabolic management center: an innovation project for the management of metabolic diseases and complications in China. J Diabetes 2019; 11(1): 11–13.

37.

Gao

Shen

, et al. A fuzzy-set qualitative comparative analysis exploration of multiple paths to users' continuous use behavior of diabetes self-management apps. Int J Med Inform 2023; 172: 105000.

38.

Hsieh

H-F

Shannon

. Three approaches to qualitative content analysis. Qual Health Res 2005; 15(9): 1277–1288.

39.

Mayring

. Qualitative content analysis. A companion to qualitative research 2004; 1(2): 159–176.

40.

Mack

. Qualitative research methods: a data collector’s field guide. Family Health International 2005.

41.

AlYahmady

Alabri

. Using NVivo for data analysis in qualitative research. International interdisciplinary journal of education 2013; 2(2): 181–186.

42.

Pereira

DMVJ

. Contributions from literature for understanding wine Marketing. Sustainability 2021; 13(13): 1.

43.

Khunti

Gomes

Pocock

, et al. Therapeutic inertia in the treatment of hyperglycaemia in patients with type 2 diabetes: a systematic review. Diabetes Obes Metab 2018; 20(2): 427–437.

44.

Bynum

WEI

Artino

ARJ

. Who Am I, and who do I strive to Be? Applying a theory of self-conscious emotions to medical education. Acad Med 2018; 93(6): 874–880.

45.

ElSayed

Aleppo

Aroda

, et al. 5. Facilitating positive health behaviors and Well-being to improve health outcomes: standards of care in diabetes-2023. Diabetes Care 2023; 46(Supple 1): S68–S96.

46.

Rogers

Aidasani

Friedes

, et al. Barriers and facilitators to the implementation of a mobile insulin titration intervention for patients with uncontrolled diabetes: a qualitative analysis. JMIR Mhealth Uhealth 2019; 7(7): e13906.

47.

Fleming

Petrie

Bergenstal

, et al. Diabetes digital app technology: Benefits, challenges, and recommendations. A Consensus Report by the European association for the study of diabetes (EASD) and the American diabetes association (ADA) diabetes technology working group. Diabetes Care 2020; 43(1): 250–260.

48.

ElSayed

Aleppo

Aroda

, et al. Summary of Revisions: standards of care in diabetes-2023. Diabetes Care 2023; 46(Suppl 1): S5–S9.

49.

Williams

Schroeder

. Popular glucose tracking apps and Use of mHealth by Latinos with diabetes: review. JMIR Mhealth Uhealth 2015; 3(3): e84.

50.

Solbrig

Jones

Kavanagh

, et al. People trying to lose weight dislike calorie counting apps and want motivational support to help them achieve their goals. Internet Interv 2017; 7: 23–31.

51.

Delone

Mclean

. The DeLone and McLean model of information systems success: a Ten-Year update. J Manag Inf Syst 2003; 19(4): 9–30.

52.

Robinson

. Trust, health care relationships, and chronic illness: a Theoretical Coalescence. Glob Qual Nurs Res 2016; 3: 2333393616664823.

53.

Chavez

Fedele

Guo

, et al. Mobile apps for the management of diabetes. Diabetes Care 2017; 40(10): e145–e146.

54.

Peng

Kononova

, et al. Habit formation in wearable activity tracker Use among older adults: qualitative study. JMIR Mhealth Uhealth 2021; 9(1): e22488.

55.

Rabbi

Pfammatter

Zhang

, et al. Automated personalized feedback for physical activity and dietary behavior change with mobile phones: a randomized controlled trial on adults. JMIR Mhealth Uhealth 2015; 3(2): e42.

56.

Katz

Price

Holland

, et al. (eds). Data, data everywhere, and still too hard to link: insights from user interactions with diabetes apps. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 2018.

57.

Gimpel

Nißen

Görlitz

. Quantifying the quantified self: a study on the motivations of patients to track their own health. 2013.

58.

Clawson

Pater

Miller

, et al. (eds). No longer wearing: investigating the abandonment of personal health-tracking technologies on craigslist. 2015. 647–658. DOI: 10.1007/s40271-012-0001-0.

59.

Kostagiolas

Kourouthanassis

Martzoukou

, et al. Information seeking behavioural paths of physicians for diabetes mellitus care: a qualitative comparative analysis of information needs, sources, and barriers. Health Syst 2018; 7(1): 13–28.

60.

Zhang

. Continuous use of fitness apps and shaping factors among college students: a mixed-method investigation. Int J Nurs Sci 2020; 7(Suppl 1): S80–S87.

61.

Daniëls

NEM

Hochstenbach

LMJ

van Zelst

, et al. Factors that influence the use of electronic diaries in health care: scoping review. JMIR Mhealth Uhealth 2021; 9(6): e19536.

62.

Xie

. Outpatient workload in China. Lancet 2013; 381(9882): 1983–1994.

63.

ElSayed

Aleppo

Aroda

, et al. 1. Improving care and promoting health in populations: standards of care in diabetes-2023. Diabetes Care 2023; 46(Supple 1): S10–S18.

64.

Holmes

Jr. Mack

Leon

, et al. The medical device innovation consortium and its goal to further the efficiency of early feasibility studies in the United States. J Endovasc Ther 2019; 26(3): 423–444.

65.

Azelton

Crowley

Vence

, et al. Digital health coaching for type 2 diabetes: randomized controlled trial of healthy at home. Front Digit Health 2021; 3: 764735.

66.

Esper

Holder-Murray

Meister

, et al. A Novel digital health platform with health coaches to optimize surgical patients: feasibility study at a large academic health system. JMIR Perioper Med 2024; 7: e52125.

67.

Fain

. 2017 national standards for diabetes self-management education and support (DSMES): revised and updated. Diabetes Educ 2017; 43(5): 439.

68.

Rose

Petrut

L'Heveder

, et al. IDF Europe's position on mobile applications in diabetes. Diabetes Res Clin Pract 2019; 149: 39–46.

69.

Xiong

Zhao

(eds). Research on credit evaluation of mobile medical APP interactive online consultation service-take haodaifu APP online payment service as an example. Journal of Physics: Conference Series. Iop Publishing, 2017.

70.

Mason

Laporte

McDonald

, et al.

Health reporting from different data sources: Does it matter for mental health?

J Ment Health Policy Econ 2023; 26(1): 33–57.

71.

Mackenzie

Heath

Vogel

, et al. Age differences in public stigma, self-stigma, and attitudes toward seeking help: a moderated mediation model. J Clin Psychol 2019; 75(12): 2259–2272.

72.

Eitel

Pihoker

Barrett

, et al. Diabetes stigma and clinical outcomes: an international review. J Endocr Soc 2024; 8(9): bvae136.

73.

Lake

Rees

Speight

. Clinical and psychosocial factors influencing retinal screening uptake among young adults with type 2 diabetes. Curr Diab Rep 2018; 18(7): 41.

74.

Bautista

Mabulay

. An in-depth exploration of how young adults' decision-making is influenced by peer pressure and conformity. A Journal Analysis presented as a final requirement For Social Psychology SOCP311 2023.

75.

Schabert

Browne

Mosely

, et al. Social stigma in diabetes A framework to understand a growing problem for an increasing epidemic. Patient. 2013; 6(1): 1–10. DOI: 10.1007/s40271-012-0001-0.

76.

Kvedar

Fogel

Elenko

, et al. Digital medicine's march on chronic disease. Nat Biotechnol 2016; 34(3): 239–246.

77.

Otanga

Semujju

Mwaniki

, et al. Peer support and social networking interventions in diabetes self-management in Kenya and Uganda: a scoping review. PLoS One 2022; 17(9): e0273722.

78.

Jahns

R-G

. Today’s diabetes apps are far away from meeting the seven best practice standards. https://research2guidance.com/todays-diabetes-apps-are-far-away-from-meeting-the-seven-best-practice-standards/ (2014).

79.

Scheibe

Reichelt

Bellmann

, et al. Acceptance factors of mobile apps for diabetes by patients aged 50 or older: a qualitative study. Medicine 2015; 20(1): 4.

80.

Shandhi

MMH

Singh

Janson

, et al. Assessment of ownership of smart devices and the acceptability of digital health data sharing. NPJ Digit Med 2024; 7(1): 44.

81.

Lai

Visaria

Østbye

, et al. Prevalence and correlates of use of digital technology for managing hypertension among older adults. J Hum Hypertens 2023; 37(1): 80–87.

82.

Huang

Chan

, et al. Associations between adoption of eHealth management module and optimal control of HbA1c in diabetes patients. NPJ Digit Med 2023; 6(1): 67.

83.

Prentice

Rayco-Solon

Moore

. Insights from the developing world: thrifty genotypes and thrifty phenotypes. Proc Nutr Soc 2005; 64(2): 153–161.

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