This paper is in the following e-collection/theme issue:

RCTs - Protocols/Proposals (eHealth) (545) Diabetes Self-Management (491) Apps, Mobile, Wearables for Diabetes (303) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1422)

Published on in Vol 11, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31652, first published .
The Impact of Mobile Health Use on the Self-care of Patients With Type 2 Diabetes: Protocol for a Randomized Controlled Trial

The Impact of Mobile Health Use on the Self-care of Patients With Type 2 Diabetes: Protocol for a Randomized Controlled Trial

The Impact of Mobile Health Use on the Self-care of Patients With Type 2 Diabetes: Protocol for a Randomized Controlled Trial

Authors of this article:

Lucija Gosak1 Author Orcid Image ;   Majda Pajnkihar1 Author Orcid Image ;   Gregor Stiglic1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

    Protocol

    Faculty of Health Sciences, University of Maribor, Maribor, Slovenia

    Corresponding Author:

    Lucija Gosak, MSc

    Faculty of Health Sciences

    University of Maribor

    Zitna 15

    Maribor, 2000

    Slovenia

    Phone: 386 2 300 47 35

    Email: lucija.gosak2@um.si


    Background: Chronic diseases are a substantial public health issue worldwide and affect an individual’s quality of life. Due to the alarming rise in type 2 diabetes, health care that was primarily focused on diagnosis and treatment of the disease is increasingly focused on prevention and self-care. Patients who adhere to a constant and strict treatment regimen (physical activity, diet, medication) and regularly monitor their health are more likely to maintain self-care and health, prevent the exacerbation of the disease, and avoid the complications of diabetes (retinopathy, diabetic feet, etc). In recent years, many innovative devices that have become increasingly present in inpatient health care, such as mobile apps, are available to help patients maintain consistency in monitoring their health status. Mobile apps make it easier for individuals to monitor their self-care and illness and follow instructions regarding disease control.

    Objective: This study aims to determine the impact of mobile app use on self-care in patients with type 2 diabetes. We will evaluate and test the usefulness of the forDiabetes app as a tool to improve the self-care of individuals with type 2 diabetes.

    Methods: We will perform a double-blind randomized controlled trial. The study will include individuals aged over 18 years diagnosed with or have regulated type 2 diabetes who are treated in family medicine practices. Additionally, the individuals included in the study should not have any acute complications due to the consequences of type 2 diabetes. They will use an Android or iOS mobile phone and a blood glucose meter during the investigation. With the help of simple randomization, individuals will be divided into the intervention and control groups. Individuals in the intervention group will use the forDiabetes mobile app to monitor their self-care for type 2 diabetes. Individuals in the control group will not receive a particular intervention. Data will be collected using the Self-care of Diabetes Inventory questionnaire and Brief Illness Perception Questionnaire. Blood sugar, blood pressure, glycated hemoglobin (HbA1c), and weight measurements will be monitored using calibrated instruments during the study by the nurses employed at the family medicine practice. Data will be collected at the beginning of the study and after a patient visits the family medicine practice.

    Results: In the first half of 2020, we have prepared a translation of the mobile app that will be used by the participants of the intervention group, as well as more detailed instructions for using the app. We have also prepared a translation of the questionnaires in Slovene. The research results will be published in 2023.

    Conclusions: This research contributes to greater visibility and usability of mobile apps for the self-care of patients with type 2 diabetes and raises awareness of the possible use of innovative methods.

    Trial Registration: Clinicaltrials.gov NCT04999189; https://clinicaltrials.gov/ct2/show/NCT04999189

    International Registered Report Identifier (IRRID): PRR1-10.2196/31652

    JMIR Res Protoc 2022;11(6):e31652

    doi:10.2196/31652

    Keywords

    diabetes; mobile application; disease management; self-care 


    Background

    Type 2 diabetes is a complex chronic disease [1,2] with an enormous global burden that has substantial implications for human health [3]. The consequences of the disease cause substantial economic and social responsibilities [4] and pose a growing public health problem [5,6]. Preventing and limiting the progression of the disease is an urgent task worldwide [7] and remains an important challenge for individuals and society [8]. The self-care of type 2 diabetes is key to containing the disease [9,10], reducing disease complications, and improving quality of life [11]. By supporting patients with type 2 diabetes in healthier self-care behaviors, we can influence the outcome of the disease [5]. The constant monitoring of diabetes and lifestyle factors can contribute to better health [12]. Many complications are the result of uncontrolled disease [13].

    The current COVID-19 pandemic affects the direction of and interrupts health care, disrupting long-term conditions including type 2 diabetes [14,15]. The need of self-care for patients with type 2 diabetes is increasingly present [16]; therefore, mobile technology has become an essential tool for promoting self-care [17]. The optimal use of mobile technologies is necessary to achieve benefits and optimal cost efficiency [18]. A mobile app strengthens self-care and contributes to better information, health education, and self-confidence in dealing with the disease [19]. Knowledge of mobile apps has been identified as an essential factor enabling independent disease management and self-care [20]. The use of new technology is one way to bridge the gap between patient needs and providing health care [21]. A mobile health app for patients with type 2 diabetes affects their knowledge of the disease, improves blood glucose control [22], and positively affects self-care [23]. In the future, mobile apps will represent an essential part of the health care system, so research in this area is needed [24]. Mobile apps show potential for disseminating self-care education [4]; improving motivation [25], disease symptom management, and patient experience [26-28]; helping patients with strict treatment requirements [29] and the adoption of a healthy lifestyle [30]; and reducing care costs [31-33].

    As a guide to the self-care of individuals with type 2 diabetes using the mobile app, we will use the Middle-Range Theory of Self-Care of Chronic Illness. Self-care is a general concept built from 3 key ideas: self-care maintenance, monitoring, and management. Maintaining self-sufficiency (or self-care maintenance) refers to an individual’s behaviors to improve well-being and maintain health and stability. Self-care monitoring refers to the process of observing oneself due to changes in signs and symptoms. Self-care management is defined as responding to signs and symptoms when they occur [34,35].

    Objectives and Hypotheses

    Objective 1 is to assess the impact of using the mobile app on the assessment of patient self-care. Hypothesis 1 states that in the intervention group of patients with type 2 diabetes, the self-sufficiency assessment at the first control visit will increase compared to the control group that did not use the mobile app.

    Objective 2 is to assess the impact of mobile app use on disease perception. Hypothesis 2 states that in the intervention group of patients with type 2 diabetes, perception at the first control visit will improve compared to the control group that did not use the mobile app.

    Objective 3 is to assess the impact of mobile app use on blood sugar and HbA1c levels. Hypothesis 3 states that in the intervention group of patients with type 2 diabetes, blood sugar and HbA1c levels at the first control visit will decrease compared to the control group that did not use the mobile app.

    Objective 4 is to assess the impact of using the mobile app on the patient’s body weight. Hypothesis 4 states that in the intervention group of patients with type 2 diabetes, the body weight at the first control visit will decrease compared to the control group that did not use the mobile app.

    Objective 5 is to assess the impact of mobile app use on the patient’s blood pressure values. Hypothesis 5 states that in the intervention group of patients with type 2 diabetes, the blood pressure value at the first control visit will decrease compared to the control group that did not use the mobile app.


    Randomized Controlled Trial Design

    To determine the effectiveness of using the mobile app on the self-care of patients with diabetes, we will conduct a double-blind randomized controlled trial. The study will include people aged over 18 years diagnosed with type 2 diabetes who are treated in family medicine practices in Slovenia. It will also include patients who have already been given some form of treatment to manage the disease and do not have chronic complications due to the disease (retinopathy, diabetic foot, nephropathy, neuropathy, etc). We will ensure this by receiving information on the patient’s health status from the medical staff. The patients will use a mobile phone and a blood glucose meter during the research period. Individuals will use the forDiabetes [36] mobile app in the intervention group. forDiabetes [36] is an existing app designed for diabetes self-care and allows the tracking and monitoring of crucial diabetes data (physical activity; high-carbohydrate foods consumed; blood glucose, blood pressure, and HbA1c levels; weight; medications; etc). Before selecting the mobile app, its quality was assessed by 2 nurses using the Mobile Application Rating Scale: user version [37]. The mobile app was rated as high quality and suitable for patients (mean 4.54, SD 0.33; on a scale out of 5) by the nurses. In accordance with the American Association of Diabetes Educators, we also assessed whether the mobile app includes self-care behaviors [38]. The mobile app contains behaviors from the awareness of the social determinants of health, integration of technology into self-care, and role of the diabetes care and education specialist.

    In the control group, individuals will not use any diabetes technologies to guide the self-care of their disease, but they will be using a blood glucose meter. The control group patients will manage their disease as before and attend scheduled checkups.

    Before the start of the study and at the follow-up visit to the family medicine practice after using the mobile app, we will perform assessments of self-care and disease perception using the Self-care of Diabetes Inventory (SCODI) [39] and Brief Illness Perception Questionnaire (Brief IPQ) [40] instruments, respectively. A nurse employed at the family medicine practice will also monitor blood sugar, blood pressure, and glycated hemoglobin (HbA1c) levels and body weight in the intervention and control groups with standardized, validated instruments. The nurse will use the standardized calibration devices according to the guidelines for each measurement. Data will be recorded at each inspection. We will also collect the data that the patients will enter daily into the mobile app (physical activity; high-carbohydrate foods consumed; blood glucose, blood pressure, and HbA1c levels; weight; medication; etc) in real time.

    The research will be carried out in family medicine practices where individuals with type 2 diabetes are treated throughout Slovenia. The study will cover at least one private and one public family medicine practice from each regional unit in Slovenia. We will use a simple randomized approach to select the family medicine practices for cooperation from a preprepared list of family medicine practices. Before conducting the research, we will obtain the necessary consent from all institutions where the study will take place to enter the family medicine practices. We will also get the required permits from the individuals involved. At the beginning of the randomized controlled trial, we will obtain the written or oral consent of the institutions to participate in the research and enter their environment. The institutions will be provided with all necessary information and the research purpose. In the introductory part of the research, the participants in the study will be informed about the purpose and goal of the study, ensuring the anonymity of the participants, the voluntary nature of participation, and the possibility of withdrawing from participation. The survey will run for 1 year. Figure 1 presents a graphical illustration of the research process.

    ‎
    Figure 1. Protocol for conducting a randomized controlled trail. HbA1c: glycated hemoglobin.
    View this figure

    Mobile App Translation

    The mobile app forDiabetes [36] includes the required self-care behaviors according to the American Association of Diabetes Educators [38] and is suitable for maintaining self-care in individuals with type 2 diabetes. Before starting the research, we have obtained written consent to use the mobile app. forDiabetes [36] is an existing app translated from English into Slovene before the research was conducted. The text was translated by 2 researchers who have the necessary knowledge in self-care and English. In the case of wording deviations, there was a discussion between the researchers to find a Slovene word as close as possible to the meaning of the English word and used as professional terminology in the Slovenian language.

    Randomization and Blinding

    Through simple randomization, the participants will be divided into the intervention and control groups, thus providing all participants with the same opportunity to be selected into any group in the study [41]. The randomization process will be blinded, as this will avoid the possibility of choice bias [42,43]. Blinded group assignment will be enabled using a group assignment software, which will allow a general random selection of the individual groups. The researcher involved in the randomization process and the patients themselves will not know to which group the patients were assigned. The medical staff will be informed about the start of the research and use of the mobile app by the individuals in the intervention group. The only difference between the intervention and control groups will be the use of the forDiabetes [36] mobile app, which the intervention group will use from the beginning of the study until the first control visit. Both groups will receive instruction regarding type 2 diabetes and the related self-care.

    Data Collection

    The initial part of the questionnaire consists of questions about the patient’s demographic data and data on the patient’s support from the medical staff. The first part of the questionnaire will cover the assessment of self-care. Self-care in patients with type 2 diabetes will be assessed using the SCODI instrument [39]. The tool consists of 40 assumptions classified into 4 dimensions: self-care maintenance (12 assumptions), self-care implementation (8 assumptions), self-care monitoring (9 assumptions), and self-confidence (11 assumptions). The instrument is assessed using a Likert scale, where a higher score represents better self-care [39]. We will also use the Brief IPQ scale [40] to assess disease perception. The questionnaire rapidly assesses disease perception and measures the patients’ cognitive and emotional representations of their disease. The questionnaire contains 8 questions graded on a 10-point scale and 1 open-ended question. There are 5 questions that assess the cognitive perceptions of the disease: consequences (point 1), timeline (point 2), personal control (point 3), treatment control (point 4), and identity (point 5); 2 questions that assess emotional representation: care (point 6) and emotions (point 8); and 1 question that estimates the comprehensibility of the disease (point 7). The assessment of causal representation is based on an open response that requires the patients to indicate the 3 most important causal factors in their disease (point 9) [40]. The nurses employed at the family medicine practices will use standardized, calibrated devices according to the guidelines to measure blood sugar, blood pressure, and HbA1c levels and body weight. Data will be recorded at each control check.

    The questionnaires were translated using the reverse translation method into English. This ensured the adequacy and consistency of the translated questionnaire. It was first translated from English into Slovene independently by 2 translators. One of the translators involved had expertise in nursing, and the other had the necessary knowledge of the standard English language. Thus, we obtained 2 translation versions, which were merged in the next step through review and consultations. In the last step, 2 experts with the necessary English knowledge translated a standard Slovenian questionnaire into English and combined it into a familiar form. Thus, we obtained 2 translated questionnaires in English, which we subsequently incorporated into a standard format [44,45]. The final version of this translated questionnaire will need to be preconfirmed and tested on a small sample, and the subsequent corrections will be tested on a large representative sample of respondents [46]. We will carry out the validation of the questionnaire. To analyze the reliability of the questionnaire, we will calculate Cronbach α and perform confirmatory factor analysis. Cronbach α measures intrinsic reliability among multiple elements and assesses how reliable the questionnaire responses are [47]. If the Cronbach α value is low (close to 0), it means that some or all of the items do not measure the same dimension [47-49]. The content validation process will consist of the following steps: the preparation of a content review form, selection of an expert review team, implementation of content review, review of domains and elements, determination of the rating for each item, and calculation of Content Validity Index (CVI) [50]. The content validity will be assessed by a nurse employed at the family medicine practice with knowledge of type 2 diabetes self-care. To assess the substantive validity of the questionnaire, we will use the index of substantive validity for individual statements (Item-CVI) and the entire questionnaire (Scale-level CVI). We will use a 4-point scale for evaluation [50]. Item-CVI results higher than 0.78 from 3 or more experts in assessing an individual statement represent good substantive validity [51]. Scale-level CVI results of 0.80 or more indicate good substantive validity [52].

    Inclusion Criteria

    A randomized controlled trial will be conducted in family medicine practices where individuals with type 2 diabetes are treated throughout Slovenia. There are 10 regional units of the Health Insurance Institute of Slovenia, with 241 private and 656 public health institutions [53]. The research will cover 1 family medicine practice from each regional unit. According to the data from January to September 2018, there were 28,593 treatments of individuals in connection with type 2 diabetes conducted in family medicine practices [54]. This number was used to calculate the sample size, which was calculated using a sample size calculator (Raosoft) [55] that has been used in many similar health research studies [56-59]. We used a power analysis and entered the necessary data with a 95% error rate and 5% confidence level. The required minimum sample size is 380 participants. We will include individuals aged over 18 years with type 2 diabetes who have already been given treatment. Additionally, there should be no acute complications due to the consequences of type 2 diabetes in the individuals included in the study. They must use a mobile phone and a blood glucose meter during the research period.

    Statistical Analysis

    The sample will be described with descriptive statistics, and the explanatory variables will be presented with frequencies and percentages. In contrast, the numerical variables will be presented with the mean value, SD, and minimum and maximum values. To test the relationship between different variables, we will use the Mann-Whitney U test in the case of an uneven distribution of variables or the t test of independent samples in an even distribution of variables. The significance level of α=.05 will test the hypotheses.

    Ethics Approval

    We received permission from The Republic of Slovenia National Medical Ethics Committee (03/5R-2021) for the primary research. We will also obtain the necessary consent from all institutions and participants in a randomized controlled trial. We will obtain permits from the institutions to enter the family medicine practices to conduct the research. We will also obtain consent from the participants to participate in the study. Before starting the analysis, we received written authorization to use the mobile app forDiabetes [36]. We also obtained permission from the authors to use and translate the questionnaires SCODI [39] and Brief IPQ [40]. In the introductory part of the research, the research participants will be acquainted with the purpose and goal of the study, ensuring the anonymity of the participants, voluntary nature of participation, and possibility of withdrawing from participation. Participants who submit a completed questionnaire will consent to the research and use of their data. The data will be securely stored and used only for research and publication, and only the researchers involved will have access to the actual data. The data will be kept for 10 years. We will ensure the anonymity of the participants throughout the research; it will not be possible to identify a person and institution or other demographic data from the results presented. The study does not pose a risk to the participants and represents a minimal burden. We will also consider the principles of legality, fairness, proportionality, accuracy, and timeliness of the data during the research


    Before the current phase of the research, we have prepared a translation of the mobile app that will be used by the participants of the intervention group, as well as more detailed instructions for using the app. We have also prepared a translation of the questionnaires in Slovene. The research results will be published in 2023.


    Expected Findings

    Adherence to chronic management measures is essential for maintaining good health outcomes [60]. By 2045, the number of patients with diabetes will rise to approximately 629 million [61]. Mobile apps provide motivation and support for self-care in these patients [62], but there is still a lack of knowledge about their actual use [63].

    Based on the described methodological process, we will perform a randomized controlled trial to determine the effectiveness of a mobile app and its impact on patients with diabetes. The research represents a unique opportunity to use and integrate mobile apps in the treatments of individuals with type 2 diabetes to solve challenges and achieve better self-care. We will enable the use of an efficient and evidence-based mobile app that is suitable for users’ needs and includes the concept of self-care in the framework of mobile health. The research will help to gain new knowledge in integrating mobile technology into the life of an individual with type 2 diabetes.

    Limitations

    The main limitation is that we will only include patients with controlled and managed type 2 diabetes in the study, which means that we will examine only a specific part of the population. The study will also have only patients treated in family medicine practices, which may prevent the possibility of generalization to all people with type 2 diabetes.

    Having both control and intervention groups at the same family medicine practices may provide bias, as this will not conceal the allocation of an intervention in a randomized controlled trial. Researchers will know in which group the participants were assigned, as these participants will carry out the necessary training for the use of the mobile app and other interventions. The research will use a questionnaire to assess the participants’ self-care and perception of the disease, which can provide socially expected and desirable answers.

    Our study contains the following assumptions. People with type 2 diabetes have deviations or shortcomings in each concept of self-care. The app will affect a patient’s self-care with type 2 diabetes and other critical clinical measures. Self-care and disease perception are measurable and that the translated questionnaire will be helpful in our research. Medical professionals, employees in family medicine practices, and individuals with type 2 diabetes will be willing to participate in the study. People with type 2 diabetes will actively use the mobile app and monitor their health through data entry. The results expected during the study are changes in self-care; disease perception; blood sugar, blood pressure, and HbA1c levels; and measured body weight.

    Acknowledgments

    This work was supported by the “knowledge through creative pathways 2016-2020” scheme cofounded by the European Union from the European Social Fund and the Republic of Slovenia and the Slovenian Research Agency (grants N2-0101 and P2-0057).

    Conflicts of Interest

    None declared.

    1. Jacoby J. Systematic review of mobile phone apps currently available to Norwegian users to support diabetes self-management. In: HCI International 2019 - Posters. Cham, Switzerland: Springer; 2019 Jul 06 Presented at: HCII 2019: International Conference on Human-Computer Interaction; July 26-31, 2019; Orlando, FL p. 457-466. [CrossRef]
    2. Lambrinou E, Hansen TB, Beulens JW. Lifestyle factors, self-management and patient empowerment in diabetes care. Eur J Prev Cardiol 2019 Dec;26(2_suppl):55-63. [CrossRef] [Medline]
    3. Blaslov K, Naranđa FS, Kruljac I, Renar IP. Treatment approach to type 2 diabetes: past, present and future. World J Diabetes 2018 Dec 15;9(12):209-219 [FREE Full text] [CrossRef] [Medline]
    4. Zhang Y, Liu C, Luo S, Huang J, Li X, Zhou Z. Effectiveness of Lilly Connected Care Program (LCCP) app-based diabetes education for patients with type 2 diabetes treated with insulin: retrospective real-world study. JMIR mHealth uHealth 2020 Mar 06;8(3):e17455 [FREE Full text] [CrossRef] [Medline]
    5. Young HM, Miyamoto S, Dharmar M, Tang-Feldman Y. 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 Mar 02;8(3):e16665 [FREE Full text] [CrossRef] [Medline]
    6. Grady PA, Gough LL. Self-management: a comprehensive approach to management of chronic conditions. Am J Public Health 2014 Aug;104(8):e25-e31. [CrossRef] [Medline]
    7. Yamaguchi S, Waki K, Nannya Y, Nangaku M, Kadowaki T, Ohe K. Usage patterns of GlucoNote, a self-management smartphone app, based on ResearchKit for patients with type 2 diabetes and prediabetes. JMIR mHealth uHealth 2019 Apr 24;7(4):e13204 [FREE Full text] [CrossRef] [Medline]
    8. Holmen H, Wahl AK, Småstuen MC, Ribu L. Tailored communication within mobile apps for diabetes self-management: a systematic review. J Med Internet Res 2017 Jun 23;19(6):e227 [FREE Full text] [CrossRef] [Medline]
    9. Hailu E, Mariam WH, Belachew T, Birhanu Z. Self-care practice and glycaemic control amongst adults with diabetes at the Jimma University Specialized Hospital in south-west Ethiopia: a cross-sectional study. Afr J Prim Health Care Fam Med 2012;4(1):311. [CrossRef]
    10. Bonger Z, Shiferaw S, Tariku EZ. Adherence to diabetic self-care practices and its associated factors among patients with type 2 diabetes in Addis Ababa, Ethiopia. Patient Prefer Adherence 2018;12:963-970 [FREE Full text] [CrossRef] [Medline]
    11. Osokpo O, Riegel B. Cultural factors influencing self-care by persons with cardiovascular disease: an integrative review. Int J Nurs Stud 2021;116:103383. [CrossRef] [Medline]
    12. Spanakis EG, Chiarugi F, Kouroubali A, Spat S, Beck P, Asanin S, et al. Diabetes management using modern information and communication technologies and new care models. Interact J Med Res 2012;1(2):e8 [FREE Full text] [CrossRef] [Medline]
    13. Shan R, Sarkar S, Martin SS. Digital health technology and mobile devices for the management of diabetes mellitus: state of the art. Diabetologia 2019;62(6):877-887. [CrossRef] [Medline]
    14. Hartmann-Boyce J, Morris E, Goyder C, Kinton J, Perring J, Nunan D, et al. Managing diabetes during the COVID-19 pandemic. The Centre for Evidence-Based Medicine. 2020 Apr 08.   URL: https://www.cebm.net/covid-19/managing-diabetes-during-the-covid-19-pandemic/ [accessed 2021-03-17]
    15. Hartmann-Boyce J, Mahtani KR. Supporting people with long-term conditions (LTCs) during national emergencies. The Centre for Evidence-Based Medicine. 2020 Mar 25.   URL: https:/​/www.​cebm.net/​covid-19/​supporting-people-with-long-term-conditions-ltcs-during-national-emergencies/​ [accessed 2021-03-17]
    16. Doupis J, Festas G, Tsilivigos C, Efthymiou V, Kokkinos A. Smartphone-based technology in diabetes management. Diabetes Ther 2020;11(3):607-619 [FREE Full text] [CrossRef] [Medline]
    17. Torbjørnsen A, Jenum AK, Småstuen MC, Arsand E, Holmen H, Wahl AK, et al. A low-intensity mobile health intervention with and without health counseling for persons with type 2 diabetes, part 1: baseline and short-term results from a randomized controlled trial in the Norwegian part of RENEWING HEALTH. JMIR mHealth uHealth 2014 Dec 11;2(4):e52 [FREE Full text] [CrossRef] [Medline]
    18. Alcántara-Aragón V. Improving patient self-care using diabetes technologies. Ther Adv Endocrinol Metab 2019;10:2042018818824215 [FREE Full text] [CrossRef] [Medline]
    19. Bonoto BC, de Araújo VE, Godói IP, de Lemos LLP, Godman B, Bennie M, et al. Efficacy of mobile apps to support the care of patients with diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials. JMIR mHealth uHealth 2017;5(3):e4 [FREE Full text] [CrossRef] [Medline]
    20. Adu MD, Malabu UH, Malau-Aduli AEO, Malau-Aduli BS. Enablers and barriers to effective diabetes self-management: a multi-national investigation. PLoS One 2019;14(6):e0217771 [FREE Full text] [CrossRef] [Medline]
    21. Bonn SE, Alexandrou C, Hjörleifsdottir Steiner K, Wiklander K, Östenson CG, Löf M, et al. App-technology to increase physical activity among patients with diabetes type 2 - the DiaCert-study, a randomized controlled trial. BMC Public Health 2018;18(1):119 [FREE Full text] [CrossRef] [Medline]
    22. Wang Y, Li M, Zhao X, Pan X, Lu M, Lu J, et al. Effects of continuous care for patients with type 2 diabetes using mobile health application: A randomised controlled trial. Int J Health Plann Manage 2019 Jul 31;34(3):1025-1035. [CrossRef] [Medline]
    23. Hooshmandja M, Mohammadi A, Esteghamti A, Aliabadi K, Nili M. Effect of mobile learning (application) on self-care behaviors and blood glucose of type 2 diabetic patients. J Diabetes Metab Disord 2019 Dec 12;18(2):307-313 [FREE Full text] [CrossRef] [Medline]
    24. Holmen H, Wahl AK, Cvancarova Småstuen M, Ribu L. Tailored communication within mobile apps for diabetes self-management: a systematic review. J Med Internet Res 2017 Jun 23;19(6):e227 [FREE Full text] [CrossRef] [Medline]
    25. Fijačko N, Gosak L, Cilar L, Novšak A, Creber RM, Skok P, et al. The effects of gamification and oral self-care on oral hygiene in children: systematic search in app stores and evaluation of apps. JMIR mHealth uHealth 2020 Jul 08;8(7):e16365 [FREE Full text] [CrossRef] [Medline]
    26. Lu C, Hu Y, Xie J, Fu Q, Leigh I, Governor S, et al. The use of mobile health applications to improve patient experience: cross-sectional study in Chinese public hospitals. JMIR mHealth uHealth 2018 May 23;6(5):e126 [FREE Full text] [CrossRef] [Medline]
    27. Bene BA, O'Connor S, Mastellos N, Majeed A, Fadahunsi KP, O'Donoghue J. Impact of mobile health applications on self-management in patients with type 2 diabetes mellitus: protocol of a systematic review. BMJ Open 2019 Jun 25;9(6):e025714 [FREE Full text] [CrossRef] [Medline]
    28. Greenwood DA, Gee PM, Fatkin KJ, Peeples M. A systematic review of reviews evaluating technology-enabled diabetes self-management education and support. J Diabetes Sci Technol 2017 Sep;11(5):1015-1027 [FREE Full text] [CrossRef] [Medline]
    29. Lee J. Hype or hope for diabetes mobile health applications? Diabetes Res Clin Pract 2014 Nov;106(2):390-392. [CrossRef] [Medline]
    30. Fleming GA, Petrie JR, Bergenstal RM, Holl RW, Peters AL, Heinemann L. 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 Jan;43(1):250-260. [CrossRef] [Medline]
    31. Lewinski AA, Patel UD, Diamantidis CJ, Oakes M, Baloch K, Crowley MJ, et al. Addressing diabetes and poorly controlled hypertension: pragmatic mHealth self-management intervention. J Med Internet Res 2019 Apr 09;21(4):e12541 [FREE Full text] [CrossRef] [Medline]
    32. Robbins R, Krebs P, Jagannathan R, Jean-Louis G, Duncan DT. Health app use among US mobile phone users: analysis of trends by chronic disease status. JMIR mHealth uHealth 2017 Dec 19;5(12):e197 [FREE Full text] [CrossRef] [Medline]
    33. Wang Y, Xue H, Huang Y, Huang L, Zhang D. A systematic review of application and effectiveness of mHealth interventions for obesity and diabetes treatment and self-management. Adv Nutr 2017 May;8(3):449-462 [FREE Full text] [CrossRef] [Medline]
    34. Riegel B, Jaarsma T, Strömberg A. A middle-range theory of self-care of chronic illness. ANS Adv Nurs Sci 2012;35(3):194-204. [CrossRef] [Medline]
    35. Riegel B, Jaarsma T, Stromberg A. Theory of self-care of chronic illness. In: Smith MJ, Liehr PR, editors. Middle Range Theory for Nursing. 4th ed. Cham, Switzerland: Springer; Feb 2018:341-353.
    36. Tessera Multimedia. forDiabetes.   URL: https://fordiabetes.app/ [accessed 2021-03-17]
    37. Stoyanov SR, Hides L, Kavanagh DJ, Wilson H. Development and validation of the user version of the Mobile Application Rating Scale (uMARS). JMIR mHealth uHealth 2016;4(2):e72 [FREE Full text] [CrossRef] [Medline]
    38. Tomky D, Cypress M. AADE7 self-care behaviors: American Association of Diabetes Educators (AADE) position statement. American Association of Diabetes Educators. 2018.   URL: https:/​/www.​diabeteseducator.org/​docs/​default-source/​practice/​practice-resources/​position-statements/​aade7-self-care-behaviors-position-statement.​pdf?sfvrsn=6 [accessed 2021-03-17]
    39. Ausili D, Barbaranelli C, Rossi E, Rebora P, Fabrizi D, Coghi C, et al. Development and psychometric testing of a theory-based tool to measure self-care in diabetes patients: the Self-Care of Diabetes Inventory. BMC Endocr Disord 2017 Oct 16;17(1):66 [FREE Full text] [CrossRef] [Medline]
    40. Broadbent E, Petrie KJ, Main J, Weinman J. The brief illness perception questionnaire. J Psychosom Res 2006 Jun;60(6):631-637. [CrossRef] [Medline]
    41. Sil A, Kumar P, Kumar R, Das NK. Selection of control, randomization, blinding, and allocation concealment. Indian Dermatol Online J 2019;10(5):601-605 [FREE Full text] [CrossRef] [Medline]
    42. Suresh K. An overview of randomization techniques: an unbiased assessment of outcome in clinical research. J Hum Reprod Sci 2011 Jan;4(1):8-11 [FREE Full text] [CrossRef] [Medline]
    43. Schulz KF, Grimes DA. Allocation concealment in randomised trials: defending against deciphering. The Lancet 2002 Feb 16;359(9306):614-618. [CrossRef] [Medline]
    44. Riegel B, Jaarsma T, Strömberg A, Vellone E, Dickson V. Translation and back translation of self-care instruments. Self-Care Measures.   URL: https://self-care-measures.com/instrument-translation-process/ [accessed 2021-03-17]
    45. Polit DF, Beck CT. Nursing Research: Generating and Assessing Evidence for Nursing Practice. 9th ed. Philadelphia, PA: Lippincott, Williams & Wilkins; 2012.
    46. Tsang S, Royse CF, Terkawi AS. Guidelines for developing, translating, and validating a questionnaire in perioperative and pain medicine. Saudi J Anaesth 2017 May;11(Suppl 1):S80-S89 [FREE Full text] [CrossRef] [Medline]
    47. Bujang MA, Omar ED, Baharum NA. A review on sample size determination for Cronbach's alpha test: a simple guide for researchers. Malays J Med Sci 2018;25(6):85-99 [FREE Full text] [CrossRef] [Medline]
    48. Leontitsis A, Pagge J. A simulation approach on Cronbach's alpha statistical significance. Mathematics and Computers in Simulation 2007;73(5):336-340. [CrossRef]
    49. Gliem JA, Gliem RR. Calculating, interpreting, and reporting Cronbach's alpha reliability coefficient for Likert-type scales. 2003 Presented at: Midwest Research-to-Practice Conference in Adult, Continuing, and Community Education; October 8-10, 2003; Columbus, OH p. 82-88   URL: https:/​/scholarworks.​iupui.edu/​bitstream/​handle/​1805/​344/​Gliem%20%26%20Gliem.​pdf?sequence=1&isAllowed=y
    50. Yusoff MSB. ABC of content validation and content validity index calculation. EIMJ 2019 Jun 28;11(2):49-54. [CrossRef]
    51. Polit DF, Beck CT. The content validity index: are you sure you know what's being reported? Critique and recommendations. Res Nurs Health 2006 Oct;29(5):489-497. [CrossRef] [Medline]
    52. Polit DF, Beck CT, Owen SV. Is the CVI an acceptable indicator of content validity? appraisal and recommendations. Res Nurs Health 2007 Aug;30(4):459-467. [CrossRef] [Medline]
    53. Ministrstvo za zdravje. Seznam ambulant. Projekt Ministrstva za zdravje: referenčne ambulante družinske medicine. 2020.   URL: http://www.referencna-ambulanta.si/?page_id=5 [accessed 2021-03-17]
    54. Ministrstvo za zdravje. Ucinkovitost dela ambulant družinske medicine za področje nalog diplomiranih medicinskih sester. Projekt Ministrstva za zdravje: referenčne ambulante družinske medicine. 2019 Jan.   URL: https:/​/www.​gov.si/​assets/​ministrstva/​ MZ/​DOKUMENTI/​Organizacija-zdravstvenega-varstva/​Mreza/​Porocilo-o-ucinkovitosti-ambulant-druzinske-medicine.​pdf [accessed 2021-03-17]
    55. Database web survey software for gathering information 2021. Raosoft.   URL: http://www.raosoft.com/ [accessed 2021-03-17]
    56. Antonio-Zancajo L, Montero J, Albaladejo A, Oteo-Calatayud MD, Alvarado-Lorenzo A. Pain and oral-health-related quality of life in orthodontic patients during initial therapy with conventional, low-friction, and lingual brackets and aligners (Invisalign): a prospective clinical study. J Clin Med 2020 Jul 03;9(7):2088 [FREE Full text] [CrossRef] [Medline]
    57. Mukeshimana MM, Nkosi ZZ. Communities' knowledge and perceptions of type two diabetes mellitus in Rwanda: a questionnaire survey. J Clin Nurs 2014;23(3-4):541-549. [CrossRef] [Medline]
    58. Olowofela A, Isah AO. Antihypertensive medicines prescriptions before and after the Nigeria Hypertension Society guidelines and prescriber's awareness of the guideline. Niger Med J 2017;58(3):107-113 [FREE Full text] [CrossRef] [Medline]
    59. Saaqib S, Iqbal A, Naheed M, Saeed T, Khalid M. A randomized controlled trial of cystoinflation to prevent bladder injury in the adhesive disease of multiple caesarean sections. Sci Rep 2020 Sep 17;10(1):15297 [FREE Full text] [CrossRef] [Medline]
    60. Hamine S, Gerth-Guyette E, Faulx D, Green BB, Ginsburg AS. Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. J Med Internet Res 2015;17(2):e52 [FREE Full text] [CrossRef] [Medline]
    61. Elflein J. Statista. 2021 Feb 18.   URL: https://www.statista.com/topics/1723/diabetes/ [accessed 2021-03-17]
    62. Veazie S, Winchell K, Gilbert J, Paynter R, Ivlev I, Eden KB, et al. Rapid evidence review of mobile applications for self-management of diabetes. J Gen Intern Med 2018 Jul;33(7):1167-1176 [FREE Full text] [CrossRef] [Medline]
    63. Trawley S, Baptista S, Browne JL, Pouwer F, Speight J. The use of mobile applications among adults with type 1 and type 2 diabetes: results from the second MILES-Australia (MILES-2) study. Diabetes Technol Ther 2017 Dec;19(12):730-738. [CrossRef] [Medline]

    ‎
    Brief IPQ: Brief Illness Perception Questionnaire
    CVI: Content Validity Index
    HbA1c: glycated hemoglobin
    SCODI: Self-Care of Diabetes Inventory

    Edited by T Leung; submitted 30.08.21; peer-reviewed by M Peeples, E Opoku-Agyemang; comments to author 24.10.21; revised version received 04.03.22; accepted 29.03.22; published 17.06.22

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    ©Lucija Gosak, Majda Pajnkihar, Gregor Stiglic. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 17.06.2022.

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