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Abdelmalak N, Burns J, Suhlrie L, Laxy M, Stephan AJ. Consideration of inequalities in effectiveness trials of mHealth applications - a systematic assessment of studies from an umbrella review. Int J Equity Health 2024; 23:181. [PMID: 39261871 PMCID: PMC11389088 DOI: 10.1186/s12939-024-02267-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 09/01/2024] [Indexed: 09/13/2024] Open
Abstract
BACKGROUND The growing use of mobile health applications (apps) for managing diabetes and hypertension entails an increased need to understand their effectiveness among different population groups. It is unclear if efficacy and effectiveness trials currently provide evidence of differential effectiveness, and if they do, a summary of such evidence is missing. Our study identified to what extent sociocultural and socioeconomic inequalities were considered in effectiveness trials of mobile health apps in diabetic and hypertensive patients and if these inequalities moderated app effectiveness. METHODS We built on our recent umbrella review that synthesized systematic reviews (SRs) of randomized controlled trials (RCTs) on the effectiveness of health apps. Using standard SR methodologies, we identified and assessed all primary RCTs from these SRs that focused on diabetes and/or hypertension and reported on health-related outcomes and inequality-related characteristics across intervention arms. We used the PROGRESS-Plus framework to define inequality-related characteristics that affect health opportunities and outcomes. We used harvest plots to summarize the subgroups (stratified analyses or interaction terms) on moderating effects of PROGRESS-Plus. We assessed study quality using the Risk of Bias 2 tool. RESULTS We included 72 published articles of 65 unique RCTs. Gender, age, and education were the most frequently described PROGRESS-Plus characteristics at baseline in more than half of the studies. Ethnicity and occupation followed in 21 and 15 RCTs, respectively. Seven trials investigated the moderating effect of age, gender or ethnicity on app effectiveness through subgroup analyses. Results were equivocal and covered a heterogenous set of outcomes. Results showed some concerns for a high risk of bias, mostly because participants could not be blinded to their intervention allocation. CONCLUSIONS Besides frequently available gender, age, and education descriptives, other relevant sociocultural or socioeconomic characteristics were neither sufficiently reported nor analyzed. We encourage researchers to investigate how these characteristics moderate the effectiveness of health apps to better understand how effect heterogeneity for apps across different sociocultural or socioeconomic groups affects inequalities, to support more equitable management of non-communicable diseases in increasingly digitalized systems. REGISTRATION https://osf.io/89dhy/ .
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Affiliation(s)
- Nancy Abdelmalak
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany.
| | - Jacob Burns
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Laura Suhlrie
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Michael Laxy
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Anna-Janina Stephan
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
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Shen Y, Wang S, Shen Y, Tan S, Dong Y, Qin W, Zhuang Y. Evaluating the Usability of mHealth Apps: An Evaluation Model Based on Task Analysis Methods and Eye Movement Data. Healthcare (Basel) 2024; 12:1310. [PMID: 38998845 PMCID: PMC11241497 DOI: 10.3390/healthcare12131310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 06/24/2024] [Accepted: 06/26/2024] [Indexed: 07/14/2024] Open
Abstract
Advancements in information technology have facilitated the emergence of mHealth apps as crucial tools for health management and chronic disease prevention. This research work focuses on mHealth apps for the management of diabetes by patients on their own. Given that China has the highest number of diabetes patients in the world, with 141 million people and a prevalence rate of 12.8% (mentioned in the Global Overview of Diabetes), the development of a usability research methodology to assess and validate the user-friendliness of apps is necessary. This study describes a usability evaluation model that combines task analysis methods and eye movement data. A blood glucose recording application was designed to be evaluated. The evaluation was designed based on the model, and the feasibility of the model was demonstrated by comparing the usability of the blood glucose logging application before and after a prototype modification based on the improvement suggestions derived from the evaluation. Tests showed that an improvement plan based on error logs and post-task questionnaires for task analysis improves interaction usability by about 24%, in addition to an improvement plan based on eye movement data analysis for hotspot movement acceleration that improves information access usability by about 15%. The results demonstrate that this study presents a usability evaluation model for mHealth apps that enables the effective evaluation of the usability of mHealth apps.
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Affiliation(s)
- Yichun Shen
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Shuyi Wang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Yuhan Shen
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Shulian Tan
- The Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Yue Dong
- The Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Wei Qin
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Yiwei Zhuang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
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Johari SM, Razalli NH, Chua KJ, Shahar S. The efficacy of self-monitoring of blood glucose (SMBG) intervention package through a subscription model among type-2 diabetes mellitus in Malaysia: a preliminary trial. Diabetol Metab Syndr 2024; 16:135. [PMID: 38902819 PMCID: PMC11191324 DOI: 10.1186/s13098-024-01379-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 06/11/2024] [Indexed: 06/22/2024] Open
Abstract
BACKGROUND The aim of this study was to determine the effect of a Self-Monitoring Blood Glucose (SMBG) intervention package through a subscription model in improving HbA1c and health parameters among type-2 diabetes mellitus (T2DM) individuals in Malaysia. METHODS This is a quasi-experimental study involving a total number of 111 individuals with T2DM (mean age 57.0 ± 11.7 years, 61% men) who were assigned to intervention (n = 51) and control (n = 60) groups. The intervention group participants were the subscribers of SugO365 program which provided a personalized care service based on self-recorded blood glucose values. Subscribers received a Contour® Plus One glucometer which can connect to Health2Sync mobile app to capture all blood glucose readings as well as physical and virtual follow up with dietitians, nutritionists, and pharmacists for 6 months. Outcome measures were body weight, body mass index (BMI), random blood glucose (RBG), glycated haemoglobin (HbA1c) and health-related quality of life (HRQoL, assessed by SF-36 questionnaire). Data were measured at baseline, third and sixth months. RESULTS Repeated-measure analysis of covariance showed significant improvement in HbA1c level (ƞp2 = 0.045, p = 0.008) in the intervention (baseline mean 7.7% ± 1.1%; end mean 7.3% ± 1.3%) as compared to control (baseline mean 7.7% ± 0.9%; end mean 8.1% ± 1.6%) group. Similar trend was observed for Role Emotional domain of the quality of life (ƞp2 = 0.047, p = 0.023) in the intervention (baseline mean 62.8 ± 35.1, end mean 86.3 ± 21.3) compared to control (baseline mean group 70.5 ± 33.8; end mean 78.4 ± 27.3) group. Negative association was found in HbA1c changes using Z-score and Physical Function domain (r = - 0.217, p = 0.022). CONCLUSION A 6 months SMBG intervention package through a subscription model improved blood glucose control as measured by HbA1c and health-related quality of life, particularly the Role Emotional domain. Elevated HbA1c levels are correlated with decreased physical function.There is a need to further examine the efficacy of SMBG intervention package using a larger sample and a longer period of intervention and to determine its cost efficacy.
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Affiliation(s)
| | - Nurul Huda Razalli
- Dietetic Program, Centre for Healthy Aging and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300, Kuala Lumpur, Malaysia.
| | | | - Suzana Shahar
- Dietetic Program, Centre for Healthy Aging and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300, Kuala Lumpur, Malaysia
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Glynn L, Mc Cann M, Mc Cabe C. Smartphone applications supporting self-management programme for adults with Chronic Obstructive Pulmonary Disease: A Scoping Review. PLOS DIGITAL HEALTH 2024; 3:e0000532. [PMID: 38870123 PMCID: PMC11175531 DOI: 10.1371/journal.pdig.0000532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2024]
Abstract
INTRODUCTION Chronic Obstructive Pulmonary Disease (COPD) significantly impacts on both the quality and quantity of life for patients due to frequent exacerbations requiring hospital admissions resulting in increased morbidity and mortality. A self-management programme purpose is to increase one's knowledge, confidence, and skills to self-manage their chronic illness such as COPD. OBJECTIVE The objective of this review will therefore answer the following research question: What is the current literature pertaining to the use of a smartphone app in supporting a comprehensive self-management programme among COPD patients? A preliminary search was conducted in, Medline, Embase and CINAHL databases to ascertain index terms and keywords. Following this a rigorous search was carried out on Medline, Embase, CINAHL, Web of Science and ASSIA. The findings from this search are presented in tabular form using the PRSIMA flow diagram. RESULTS In this review, fifteen studies met the inclusion criteria. Across all studies participants engaged with the app and developed self-management skills and knowledge to manage their chronic illness. However, engagement with the app without third party involvement declined over time. Technical issues did not cause harm to participants but in some cases contributed to reduced engagement. Smartphone self-management apps empowered a cohort of COPD participants to engage in managing their chronic illness which proved useful in detecting exacerbations earlier resulting in reducing the need for hospitalisations over a three-to-six-month period. By reducing hospitalisations incurred a cost savings for health care and an improved quality and quantity of life for these participants. CONCLUSION It is evident from the literature that smartphone self-management apps may positively influence participants self-management decisions in terms of knowledge, increase physical activity, self-efficacy that may result in reduced hospitalisation and improved quality of life. It is clear that technical issues and sustained engagement over longer periods of time remains a challenge.
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Affiliation(s)
- Lisa Glynn
- School of Nursing and Midwifery, University of Galway, Ireland
| | - Margaret Mc Cann
- School of Nursing and Midwifery, Trinity College, Dublin 2, Ireland
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Liu F, Li J, Li X, Yang Z, Wang W, Zhao L, Wu T, Huang C, Xu Y. Efficacy of telemedicine intervention in the self-management of patients with type 2 diabetes: a systematic review and meta-analysis. Front Public Health 2024; 12:1405770. [PMID: 38835608 PMCID: PMC11148367 DOI: 10.3389/fpubh.2024.1405770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Accepted: 05/01/2024] [Indexed: 06/06/2024] Open
Abstract
Purpose We aimed to report the latest and largest pooled analyses and evidence updates to assess the effectiveness of telemedicine interventions for self-management (DSM) in patients with type 2 diabetes mellitus (T2DM). Methods A systematic literature search was conducted using PubMed, Cochrane, Embase, and Web of Science in December 2023. We included randomized controlled trials (RCTs) of adults (≥18 years of age) diagnosed with T2DM where the intervention was the application of telemedicine. The Cochrane Risk of Bias Assessment was used to evaluate quality. The study's main outcome indicators were glycosylated hemoglobin (HbA1c) and diabetes self-management (DSM) capacity. Results A total of 17 eligible articles, comprising 20 studies and 1,456 patients (734 in the intervention group and 722 in the control group), were included in the evidence synthesis. The baseline characteristics of both groups were similar in all outcomes. Comprehensive analyses showed post-intervention decreases in HbA1c, 2-h postprandial glucose, systolic and diastolic blood pressure, increases in Diabetes Self- Care activities, DSM competencies based on dietary and medication adherence, and improvements in overall DSM scores, all of which were statistically significant. While no statistically significant differences were observed in body mass index, lipids, and other DSM dimensions. Based on subgroup analyses, app-based experimental interventions targeting under 60 years old populations in Asia and North America were found to be more effective and less heterogeneity in the short term (<6 months of intervention). Conclusion Telemedicine interventions may assist patients with T2DM in enhancing their DSM and improving their HbA1c levels. Clinician can use various telemedicine interventions to enhance DSM in T2DM patients, considering local circumstances. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/, CRD42024508522.
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Affiliation(s)
- Fengzhao Liu
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jixin Li
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiangyu Li
- Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhenyu Yang
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Wenru Wang
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Lijuan Zhao
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Tao Wu
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Chengcheng Huang
- Department of Endocrinology, Shandong University of Traditional Chinese Medicine Affiliated Hospital, Jinan, China
| | - Yunsheng Xu
- Department of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
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Hironaka J, Okada H, Minamida M, Kondo Y, Nakajima H, Majima S, Kitagawa N, Okamura T, Senmaru T, Ushigome E, Nakanishi N, Hamada K, Nojiri T, Hamaguchi M, Fukui M. Impact of an online nutrition management application service on glycaemic management in individuals with diabetes: A propensity-score-matched retrospective cohort study. Diabetes Obes Metab 2024; 26:1757-1765. [PMID: 38356110 DOI: 10.1111/dom.15487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/22/2024] [Accepted: 01/22/2024] [Indexed: 02/16/2024]
Abstract
AIMS To assess the impact of 'Oishi Kenko', a nutrition management application (app), on glycaemic control in patients with diabetes. MATERIALS AND METHODS A propensity-score-matched retrospective cohort study was performed using data from the KAMOGAWA-DM cohort study conducted between January and June 2022 in Japan. We analysed data from patients with type 1 and type 2 diabetes, comparing users who used the Oishi Kenko app (app group) with non-users (control group) over 3 months. RESULTS Among the 50 participants who actively used it, 47 participants in both the app and control cohorts were selected from the KAMOGAWA-DM cohort according to propensity-score matching. Within the app group, the median glycated haemoglobin (HbA1c) level was 51 mmol/mol (6.9%) at baseline, which slightly decreased to 50 mmol/mol (6.8%) at the 3-month mark (median change 0.0%). Conversely, in the control group, the baseline HbA1c level of 51 mmol/mol (6.9%) exhibited a marginal increase of 52 mmol/mol (7.0%) after 3 months (median change 0.20%). The median HbA1c level change between the groups was statistically significant, with the app group showing a significant positive change compared with the control group (p = 0.012). CONCLUSION The Oishi Kenko app effectively improved glycaemic control in patients with diabetes; hence, it may be a promising tool for patient-driven dietary management.
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Affiliation(s)
- Junya Hironaka
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Hiroshi Okada
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Megumi Minamida
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Yuriko Kondo
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Hanako Nakajima
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Saori Majima
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | | | - Takuro Okamura
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Takafumi Senmaru
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Emi Ushigome
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Naoko Nakanishi
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Kazuki Hamada
- Research and Development Division, Oishi Kenko Incorporated, Tokyo, Japan
| | - Tetsuya Nojiri
- Research and Development Division, Oishi Kenko Incorporated, Tokyo, Japan
| | - Masahide Hamaguchi
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Michiaki Fukui
- Department of Endocrinology and Metabolism, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
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Tarricone R, Petracca F, Svae L, Cucciniello M, Ciani O. Which behaviour change techniques work best for diabetes self-management mobile apps? Results from a systematic review and meta-analysis of randomised controlled trials. EBioMedicine 2024; 103:105091. [PMID: 38579364 PMCID: PMC11002812 DOI: 10.1016/j.ebiom.2024.105091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 03/14/2024] [Accepted: 03/14/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND Self-management is pivotal in addressing noncommunicable diseases, such as diabetes. The increased availability of digital behaviour change interventions (DBCIs) delivered through mobile health apps offers unprecedented opportunities to enhance self-management and improve health outcomes. However, little is known about the characteristics of DBCIs for diabetes that significantly impact glycaemic control. Therefore, our systematic review with meta-analysis aimed to summarize characteristics and behaviour change components in DBCIs for diabetes self-management and explore potential associations with metabolic outcomes. METHODS A systematic search was conducted in PubMed, Embase, the Cochrane Central Register of Controlled Trials, and Scopus to identify randomized controlled trials published until November 2023. The main outcome variable was the change in the mean difference of HbA1c levels between baseline and follow-up across intervention and control groups. Random-effects meta-regression was used to explore variation in glycaemic control as a function of prespecified characteristics of study designs and app interventions. FINDINGS A total of 57 studies was included in the analysis, showing a statistically significant percentage point reduction in HbA1c for the intervention group compared to the control arm (-0.36, 95% CI = -0.46 to -0.26, p < 0.001). The inclusion of "self-monitoring of behaviour" as a behaviour change technique (β = -0.22, p = 0.04) and "taking medication" as a target behaviour (β = -0.20, p = 0.05) was associated with improved metabolic outcomes. INTERPRETATION Our analyses endorse the use of diabetes self-management apps, highlighting characteristics statistically associated with intervention effectiveness and guiding the design of more effective DBCIs. FUNDING This project received funding from the European Union's Horizon 2020 programme.
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Affiliation(s)
- Rosanna Tarricone
- Department of Social and Political Sciences, Bocconi University, Milan, Italy; Centre for Research on Health and Social Care Management (CERGAS), Government, Health and Not for Profit Division, SDA Bocconi School of Management, Milan, Italy
| | - Francesco Petracca
- Centre for Research on Health and Social Care Management (CERGAS), Government, Health and Not for Profit Division, SDA Bocconi School of Management, Milan, Italy.
| | - Liv Svae
- Centre for Research on Health and Social Care Management (CERGAS), Government, Health and Not for Profit Division, SDA Bocconi School of Management, Milan, Italy
| | - Maria Cucciniello
- Department of Social and Political Sciences, Bocconi University, Milan, Italy; Centre for Research on Health and Social Care Management (CERGAS), Government, Health and Not for Profit Division, SDA Bocconi School of Management, Milan, Italy
| | - Oriana Ciani
- Centre for Research on Health and Social Care Management (CERGAS), Government, Health and Not for Profit Division, SDA Bocconi School of Management, Milan, Italy
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Mendoza K, Villalobos-Daniel VE, Jáuregui A, Valero-Morales I, Hernández-Alcaraz C, Zacarías-Alejandro N, Alarcon-Guevara RO, Barquera S. Development of a crowdsourcing- and gamification-based mobile application to collect epidemiological information and promote healthy lifestyles in Mexico. Sci Rep 2024; 14:6174. [PMID: 38486091 PMCID: PMC10940696 DOI: 10.1038/s41598-024-56761-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 03/11/2024] [Indexed: 03/18/2024] Open
Abstract
We developed a mobile application to promote healthy lifestyles and collect non-communicable disease (NCD) data in Mexico. Its theoretical foundations are supported by a framework-guided literature review. With design sprints, Scrum, Model-View-Controller, and Representational State Transfer architecture, we operationalized evidence-based nutrition/physical activity information into a crowdsourcing- and gamification-based application. The application was piloted for three months to monitor the response of 520 adults. Potential improvements were characterized, considering benchmarking, expert guidance, and standards. Salud Activa (English: Active Health) has two crowdsourcing modules: Nutritional scanner, scanning products' bar codes, providing nutritional data, and allowing new product registry feeding our databases; Surveys, comprising gradually-released NCD questions. Three intervention modules were generated: Drinks diary, a beverage assessment component to receive hydration recommendations; Step counter, monitoring users' steps via Google Fit/Health-iOS; Metabolic Avatar, interconnecting modules and changing as a function of beverage and step records. The 3-month median of Salud Activa use was seven days (IQR = 3-12), up to 35% of participants completed a Survey section, and 157 food products were registered through Nutritional scanner. Better customization might benefit usability and user engagement. Quantitative and qualitative data will enhance Salud Activa's design, user uptake, and efficacy in interventions delivered through this platform.
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Affiliation(s)
- Kenny Mendoza
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Center for Nutrition and Health Research (CINyS), National Institute of Public Health (INSP), Cuernavaca, Morelos, Mexico
| | - Víctor Eduardo Villalobos-Daniel
- Center for Nutrition and Health Research (CINyS), National Institute of Public Health (INSP), Cuernavaca, Morelos, Mexico
- Department of Noncommunicable Diseases and Mental Health, Pan American Health Organization, Washington, DC, USA
| | - Alejandra Jáuregui
- Center for Nutrition and Health Research (CINyS), National Institute of Public Health (INSP), Cuernavaca, Morelos, Mexico
| | - Isabel Valero-Morales
- Center for Nutrition and Health Research (CINyS), National Institute of Public Health (INSP), Cuernavaca, Morelos, Mexico
- Queen Mary University of London, London, UK
| | - César Hernández-Alcaraz
- Center for Nutrition and Health Research (CINyS), National Institute of Public Health (INSP), Cuernavaca, Morelos, Mexico
| | | | - Ricardo Omar Alarcon-Guevara
- Center for Nutrition and Health Research (CINyS), National Institute of Public Health (INSP), Cuernavaca, Morelos, Mexico
| | - Simón Barquera
- Center for Nutrition and Health Research (CINyS), National Institute of Public Health (INSP), Cuernavaca, Morelos, Mexico.
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Lee JL, Kim Y. Evaluation of Mobile Applications for Patients with Diabetes Mellitus: A Scoping Review. Healthcare (Basel) 2024; 12:368. [PMID: 38338253 PMCID: PMC10855494 DOI: 10.3390/healthcare12030368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 01/18/2024] [Accepted: 01/29/2024] [Indexed: 02/12/2024] Open
Abstract
There has been increasing interest in mobile healthcare for diabetes management. However, there remains limited evidence regarding the effectiveness of these mobile applications (apps). This scoping review aimed to evaluate the clinical effectiveness of mobile diabetes management apps. We used the following search terms: "mobile app", "mobile application", and "diabetes". We included only articles written in English and published between January 2016 and August 2021. We identified two, six, and four articles focused on type 1 diabetes, type 2 diabetes, and both diabetes types, respectively. Five, four, and three of these studies reported on the apps' functionality, usability, and both, respectively. Our findings indicated that diabetes mobile apps allowed for convenient user experience and improved blood sugar levels in patients with diabetes. Considering these findings, usability must be comprehensively evaluated by using definitions such as the ISO9241-11 usability definition or the mobile application rating scale (MARS) when developing diabetes-related apps. For the feasibility of diabetes mobile apps, we recommend that HbA1C and self-management be included as evaluation variables. Given the increasing importance of continuous management for patients with diabetes, interventions using mobile apps are bound to become effective tools for patient-led self-management.
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Affiliation(s)
- Jung Lim Lee
- Department of Nursing, Daejeon University, Daejeon 34520, Republic of Korea;
| | - Youngji Kim
- Department of Nursing, College of Nursing and Health, Kongju National University, Gongju 32588, Republic of Korea
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Konnyu KJ, Yogasingam S, Lépine J, Sullivan K, Alabousi M, Edwards A, Hillmer M, Karunananthan S, Lavis JN, Linklater S, Manns BJ, Moher D, Mortazhejri S, Nazarali S, Paprica PA, Ramsay T, Ryan PM, Sargious P, Shojania KG, Straus SE, Tonelli M, Tricco A, Vachon B, Yu CH, Zahradnik M, Trikalinos TA, Grimshaw JM, Ivers N. Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes. Cochrane Database Syst Rev 2023; 5:CD014513. [PMID: 37254718 PMCID: PMC10233616 DOI: 10.1002/14651858.cd014513] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
BACKGROUND There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations. OBJECTIVES To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care. SEARCH METHODS We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section. SELECTION CRITERIA We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy. - System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). - Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). - Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy. DATA COLLECTION AND ANALYSIS We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors. Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available. MAIN RESULTS We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted. Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three. Combinations of the three most effective QI strategies were estimated to lead to the below effects: - PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%; - CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%; - PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg; - CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg; - TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL; - TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL. Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other). AUTHORS' CONCLUSIONS There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.
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Affiliation(s)
- Kristin J Konnyu
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Sharlini Yogasingam
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Johanie Lépine
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Katrina Sullivan
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | - Alun Edwards
- Department of Medicine, University of Calgary, Calgary, Canada
| | - Michael Hillmer
- Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
| | - Sathya Karunananthan
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, Canada
| | - John N Lavis
- McMaster Health Forum, Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - Stefanie Linklater
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Braden J Manns
- Department of Medicine and Community Health Sciences, University of Calgary, Calgary, Canada
| | - David Moher
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Sameh Mortazhejri
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - Samir Nazarali
- Department of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, Canada
| | - P Alison Paprica
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Timothy Ramsay
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | - Peter Sargious
- Department of Medicine, University of Calgary, Calgary, Canada
| | - Kaveh G Shojania
- University of Toronto Centre for Patient Safety, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Sharon E Straus
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital and University of Toronto, Toronto, Canada
| | - Marcello Tonelli
- Department of Medicine and Community Health Sciences, University of Calgary, Calgary, Canada
| | - Andrea Tricco
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital and University of Toronto, Toronto, Canada
- Epidemiology Division and Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Queen's Collaboration for Health Care Quality: A JBI Centre of Excellence, Queen's University, Kingston, Canada
| | - Brigitte Vachon
- School of Rehabilitation, Occupational Therapy Program, University of Montreal, Montreal, Canada
| | - Catherine Hy Yu
- Department of Medicine, St. Michael's Hospital, Toronto, Canada
| | - Michael Zahradnik
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Thomas A Trikalinos
- Departments of Health Services, Policy, and Practice and Biostatistics, Center for Evidence Synthesis in Health, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Jeremy M Grimshaw
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Department of Medicine, University of Ottawa, Ottawa, Canada
| | - Noah Ivers
- Department of Family and Community Medicine, Women's College Hospital, Toronto, Canada
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11
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Moschonis G, Siopis G, Jung J, Eweka E, Willems R, Kwasnicka D, Asare BYA, Kodithuwakku V, Verhaeghe N, Vedanthan R, Annemans L, Oldenburg B, Manios Y. Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials. Lancet Digit Health 2023; 5:e125-e143. [PMID: 36828606 DOI: 10.1016/s2589-7500(22)00233-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 11/21/2022] [Accepted: 11/28/2022] [Indexed: 02/24/2023]
Abstract
BACKGROUND Digital health interventions have shown promising results for the management of type 2 diabetes, but a comparison of the effectiveness and implementation of the different modes is not currently available. Therefore, this study aimed to compare the effectiveness of SMS, smartphone application, and website-based interventions on improving glycaemia in adults with type 2 diabetes and report on their reach, uptake, and feasibility. METHODS In this systematic review and meta-analysis, we searched CINAHL, Cochrane Central, Embase, MEDLINE, and PsycInfo on May 25, 2022, for randomised controlled trials (RCTs) that examined the effectiveness of digital health interventions in reducing glycated haemoglobin A1c (HbA1c) in adults with type 2 diabetes, published in English from Jan 1, 2009. Screening was carried out using Covidence, and data were extracted following Cochrane's guidelines. The primary endpoint assessed was the change in the mean (and 95% CI) plasma concentration of HbA1c at 3 months or more. Cochrane risk of bias 2 was used to assess risk of bias. Data on reach, uptake, and feasibility were summarised narratively and data on HbA1c reduction were synthesised in a meta-analysis. Grading of Recommendations, Assessment, Development, and Evaluation criteria was used to evaluate the level of evidence. The study was registered with PROSPERO, CRD42021247845. FINDINGS Of the 3236 records identified, 56 RCTs from 24 regions (n=11 486 participants), were included in the narrative synthesis, and 26 studies (n=4546 participants) in the meta-analysis. 20 studies used SMS as the primary mode of delivery of the digital health intervention, 25 used smartphone applications, and 11 implemented interventions via websites. Smartphone application interventions reported higher reach compared with SMS and website-based interventions, but website-based interventions reported higher uptake compared with SMS and smartphone application interventions. Effective interventions, in general, included people with greater severity of their condition at baseline (ie, higher HbA1c) and administration of a higher dose intensity of the intervention, such as more frequent use of smartphone applications. Overall, digital health intervention group participants had a -0·30 (95% CI -0·42 to -0·19) percentage point greater reduction in HbA1c, compared with control group participants. The difference in HbA1c reduction between groups was statistically significant when interventions were delivered through smartphone applications (-0·42% [-0·63 to -0·20]) and via SMS (-0·37% [-0·57 to -0·17]), but not when delivered via websites (-0·09% [-0·64 to 0·46]). Due to the considerable heterogeneity between included studies, the level of evidence was moderate overall. INTERPRETATION Smartphone application and SMS interventions, but not website-based interventions, were associated with better glycaemic control. However, the studies' heterogeneity should be recognised. Considering that both smartphone application and SMS interventions are effective for diabetes management, clinicians should consider factors such as reach, uptake, patient preference, and context of the intervention when deciding on the mode of delivery of the intervention. Nine in ten people worldwide own a feature phone and can receive SMS and four in five people have access to a smartphone, with numerous smartphone applications being available for diabetes management. Clinicians should familiarise themselves with this modality of programme delivery and encourage people with type 2 diabetes to use evidence-based applications for improving their self-management of diabetes. Future research needs to describe in detail the mediators and moderators of the effectiveness and implementation of SMS and smartphone application interventions, such as the optimal dose, frequency, timing, user interface, and communication mode to both further improve their effectiveness and to increase their reach, uptake, and feasibility. FUNDING EU's Horizon 2020 Research and Innovation Programme.
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Affiliation(s)
- George Moschonis
- Department of Food, Nutrition and Dietetics, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, VIC, Australia.
| | - George Siopis
- Department of Food, Nutrition and Dietetics, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, VIC, Australia; Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
| | - Jenny Jung
- Maternal, Child and Adolescent Health Program, Burnet Institute, Melbourne, VIC, Australia
| | - Evette Eweka
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Ruben Willems
- Department of Public Health and Primary Care, Faculty of Medicine, Ghent University, Ghent, Belgium
| | - Dominika Kwasnicka
- NHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | | | - Vimarsha Kodithuwakku
- NHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Nick Verhaeghe
- Department of Public Health and Primary Care, Faculty of Medicine, Ghent University, Ghent, Belgium; Research Institute for Work and Society, HIVA KU Leuven, Leuven, Belgium
| | - Rajesh Vedanthan
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Lieven Annemans
- Department of Public Health and Primary Care, Faculty of Medicine, Ghent University, Ghent, Belgium
| | - Brian Oldenburg
- Academic and Research Collaborative in Health, La Trobe University, Melbourne, VIC, Australia; NHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Yannis Manios
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece; Institute of Agri-food and Life Sciences, Hellenic Mediterranean University Research Centre, Heraklion, Greece
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12
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Stevens S, Gallagher S, Andrews T, Ashall-Payne L, Humphreys L, Leigh S. The effectiveness of digital health technologies for patients with diabetes mellitus: A systematic review. FRONTIERS IN CLINICAL DIABETES AND HEALTHCARE 2022; 3:936752. [PMID: 36992773 PMCID: PMC10012107 DOI: 10.3389/fcdhc.2022.936752] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 10/03/2022] [Indexed: 12/12/2022]
Abstract
Introduction Diabetes mellitus (DM) is a leading cause of morbidity and mortality worldwide. At the same time, digital health technologies (DHTs), which include mobile health apps (mHealth) have been rapidly gaining popularity in the self-management of chronic diseases, particularly following the COVID-19 pandemic. However, while a great variety of DM-specific mHealth apps exist on the market, the evidence supporting their clinical effectiveness is still limited. Methods A systematic review was performed. A systematic search was conducted in a major electronic database to identify randomized controlled trials (RCTs) of mHealth interventions in DM published between June 2010 and June 2020. The studies were categorized by the type of DM and impact of DM-specific mHealth apps on the management of glycated haemoglobin (HbA1c) was analysed. Results In total, 25 studies comprising 3,360 patients were included. The methodological quality of included trials was mixed. Overall, participants diagnosed with T1DM, T2DM and Prediabetes all demonstrated greater improvements in HbA1c as a result of using a DHT compared with those who experienced usual care. The analysis revealed an overall improvement in HbA1c compared with usual care, with a mean difference of -0.56% for T1DM, -0.90% for T2DM and -0.26% for Prediabetes. Conclusion DM-specific mHealth apps may reduce HbA1c levels in patients with T1DM, T2DM and Prediabetes. The review highlights a need for further research on the wider clinical effectiveness of diabetes-specific mHealth specifically within T1DM and Prediabetes. These should include measures which go beyond HbA1c, capturing outcomes including short-term glycemic variability or hypoglycemic events.
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Affiliation(s)
- Sebastian Stevens
- Research Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | - Susan Gallagher
- Research Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom
| | - Tim Andrews
- Research Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom
- Warwick Medical School (WMS), The University of Warwick, Coventry, United Kingdom
| | - Liz Ashall-Payne
- Research Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom
- Warwick Medical School (WMS), The University of Warwick, Coventry, United Kingdom
| | - Lloyd Humphreys
- Research Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom
| | - Simon Leigh
- Research Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom
- Warwick Medical School (WMS), The University of Warwick, Coventry, United Kingdom
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13
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Baradez C, Liska J, Brulle-Wohlhueter C, Pushkarna D, Baxter M, Piette J. Brief Digital Solutions in Behavior Change Interventions for Type 2 Diabetes Mellitus: A Literature Review. Diabetes Ther 2022; 13:635-649. [PMID: 35279813 PMCID: PMC8917814 DOI: 10.1007/s13300-022-01244-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 02/25/2022] [Indexed: 11/25/2022] Open
Abstract
INTRODUCTION With the advent of the COVID-19 pandemic, health systems increasingly look to digital health solutions to provide support for self-management to people with type 2 diabetes (T2D). This review aimed to assess brief digital behavior change solutions (i.e., solutions that require limited engagement or contact) for T2D, including use of behavior change techniques (BCTs) and their impact on self-care and glycemic control. METHODS A review was conducted by searching Embase and gray literature using a predefined search strategy to identify randomized controlled trials (RCT) published between January 1, 2015, and March 21, 2021. BCTs were coded using an internationally established BCT taxonomy v1 (BCTTv1). RESULTS Out of 1426 articles identified, 10 RCTs were included in qualitative synthesis. Of these, six reported significant improvements in primary outcome(s), including improved patient engagement, glycemic control, self-efficacy, and physical activity. Interventions as short as 12 min were found to be effective, and users' ability to control their preferences was noted as conducive to engagement. Almost three quarters of BCTs targeted by interventions were under the hierarchical clusters of "Feedback and monitoring," "Goals and planning," and "Shaping knowledge." Interventions that targeted fewer BCTs were at least as effective as interventions that were more comprehensive in their goals. DISCUSSION Digital behavior change solutions can successfully improve T2D self-care support and outcomes in a variety of populations including patients with low incomes, limited educational attainment, or living in rural areas. Easy-to-use interventions tailored to patient needs may be as effective as lengthy, complex, and more generalized interventions. CONCLUSIONS Brief digital solutions can improve clinical and behavioral outcomes while reducing patient burden, fitting more easily in patients' lives and potentially improving usability. As T2D patients increasingly expect access to self-care assistance between face-to-face encounters, digital support tools will play a greater role in effective diabetes management programs.
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Affiliation(s)
| | | | | | | | - Mike Baxter
- Ashford and St Peter's Hospitals NHS Foundation Trust, Chertsey, England, UK
| | - John Piette
- Department of Health Behavior and Health Education, School of Public Health, University of Michigan, 2705 Ember Way, Ann Arbor, MI, 48104, USA.
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Mokaya M, Kyallo F, Vangoitsenhoven R, Matthys C. Clinical and patient-centered implementation outcomes of mHealth interventions for type 2 diabetes in low-and-middle income countries: a systematic review. Int J Behav Nutr Phys Act 2022; 19:1. [PMID: 34991593 PMCID: PMC8734304 DOI: 10.1186/s12966-021-01238-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 12/06/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The prevalence of Type 2 Diabetes is rising in Low- and Middle-Income Countries (LMICs), affecting all age categories and resulting in huge socioeconomic implications. Mobile health (mHealth) is a potential high-impact approach to improve clinical and patient-centered outcomes despite the barriers of cost, language, literacy, and internet connectivity. Therefore, it is valuable to examine the clinical and implementation outcomes of mHealth interventions for Type 2 Diabetes in LMICs. METHODS The Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) guidelines were applied in framing and reporting the review criteria. A systematic search of Cochrane Library, Web of Science, PubMed, Scopus, and Ovid databases was performed through a combination of search terms. Randomized Controlled Trials (RCTs) and cohort studies published in English between January 2010 and August 2021 were included. Risk of bias for missing results in the included studies was assessed using the Cochrane risk-of-bias tool for randomized trials (RoB 2). Quantitative and qualitative methods were used to synthesize the results. RESULTS The search identified a total of 1161 articles. Thirty studies from 14 LMICs met the eligibility criteria. On clinical outcomes, 12 and 9 studies reported on glycated hemoglobin (HbA1c )and fasting blood glucose (FBG) respectively. Text messages was the most commonly applied mHealth approach, used in 19 out of the 30 studies. Ten out of the 12 studies (83.3%) that reported on HbA1c had a percentage difference of <0.3% between the mHealth intervention and the comparison group. Additionally, studies with longer intervention periods had higher effect size and percentage difference on HbA1c (1.52 to 2.92%). Patient-centred implementation outcomes were reported variedly, where feasibility was reported in all studies. Acceptability was reported in nine studies, appropriateness in six studies and cost in four studies. mHealth evidence reporting and assessment (mERA) guidelines were not applied in all the studies in this review. CONCLUSION: mHealth interventions in LMICs are associated with clinically significant effectiveness on HbA1 but have low effectiveness on FBG. The application of mERA guidelines may standardize reporting of patient-centered implementation outcomes in LMICs. TRIAL REGISTRATION PROSPERO: Registration ID 154209.
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Affiliation(s)
- Moses Mokaya
- Department of Human Nutrition Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
| | - Florence Kyallo
- Department of Human Nutrition Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
| | - Roman Vangoitsenhoven
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
- Department of Endocrinology, University Hospitals Leuven, Leuven, Belgium
| | - Christophe Matthys
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
- Department of Endocrinology, University Hospitals Leuven, Leuven, Belgium
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15
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Verma D, Bahurupi Y, Kant R, Singh M, Aggarwal P, Saxena V. Effect of mHealth Interventions on Glycemic Control and HbA1c Improvement among Type II Diabetes Patients in Asian Population: A Systematic Review and Meta-Analysis. Indian J Endocrinol Metab 2021; 25:484-492. [PMID: 35355920 PMCID: PMC8959192 DOI: 10.4103/ijem.ijem_387_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 12/04/2021] [Accepted: 12/10/2021] [Indexed: 11/04/2022] Open
Abstract
Introduction Due to the high prevalence of diabetes mellitus, it is pertinent to educate and inform diabetes patients about their self-management. It can be done effectively using innovative methods like mobile health (mHealth), which includes mobile applications, phone calls, and text messages. Thus, this meta-analysis was conducted to summarize the effectiveness of mHealth interventions for the management of diabetes compared with usual care in the Asian population. Materials and Methods Searches were performed in electronic databases, namely PubMed, Scopus, Embase, and Cochrane Library, in August and September 2020. Search terms used were "Diabetes Mellitus," "mHealth," "glycemic control", "HbA1c levels," and "Blood glucose levels." The primary outcome was glycated hemoglobin and blood glucose levels. Trials were pooled, and heterogeneity was quantified using the I2 statistic. Results The search yielded 3980 abstracts, of which 18 trials met the inclusion criteria. Lowering of Hba1c levels was reported in the majority of trials, which aided in Glycemic control. For post prandial blood glucose (PPBG) levels, a statistically significant reduction of value -20.13 (95%CI -35.16 to -5.10, P = 0.009, I2 = 59%) was seen in the mean in the intervention group, whereas for HbA1c levels the mean reduction in the intervention group was -0.44 (95%CI, -0.79 to 0.10, P = 0.01, I2 = 87%). Although these interventions proved beneficial for these outcomes, there was a difference in the amount of effects caused by different mHealth interventions. Conclusion This study acknowledged the effects of different mHealth interventions as per their accessibility and availability in recent years. There is a need to include more studies in future reviews to generate a larger body of evidence for the reported outcomes. The researchers should give the utmost priority to the transparency while reporting the interventions for effective interpretation of the retrieved data.
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Affiliation(s)
- Divya Verma
- School of Public Health, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Yogesh Bahurupi
- Department of Community and Family Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Ravi Kant
- Department of Internal Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Mahendra Singh
- Department of Community and Family Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Pradeep Aggarwal
- Department of Community and Family Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| | - Vartika Saxena
- Department of Community and Family Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
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16
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El-Gayar O, Ofori M, Nawar N. On the efficacy of behavior change techniques in mHealth for self-management of diabetes: A meta-analysis. J Biomed Inform 2021; 119:103839. [PMID: 34139330 DOI: 10.1016/j.jbi.2021.103839] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 06/06/2021] [Accepted: 06/09/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Diabetes prevalence has become a global crisis. Due to the substantial rise in smartphone use, a variety of mobile interventions have been developed to help improve the clinical outcomes of diabetes patients. OBJECTIVES This study seeks to examine specific behavior change theories and techniques used in the design of self-management mobile app-based interventions aimed at achieving glycemic control in type 1 and type 2 diabetes. METHODS A meta-analysis of randomized control trials published in PubMed/Medline and Web of Science between January 2010 and October 2020 was conducted using studies that included diabetes patients, reported on well-described mobile app-based interventions, compared mHealth to usual care, and evaluated glycated hemoglobin (HbA1c) at baseline and follow-up. RESULTS We reported on 21 studies with a total of 1,920 diabetes patients. Our findings show that mHealth apps led to statistically significant clinical outcomes as compared to standard care for glycemic control (-0.38, 95% CI = -0.50 to -0.25, p < 0.0001) indicating that such interventions result in a reduction in HbA1c. Interventions that used behavior theory for developing mHealth apps were not statistically different from those that did not (p = 0.18). However, increased use of behavior change techniques (BCTs) may result in slightly higher HbA1c reduction. Among all BCTs, the most effective ones appear to be "Action planning" and "Self-monitoring of outcome(s) of behavior. CONCLUSIONS The current meta-analysis provides evidence that mHealth is likely to be beneficial for diabetes patients when the right behavior change techniques are applied to realize the full advantage of the intervention. Further investigation of the role of theory in the design of mHealth app-based interventions is warranted.
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Abstract
PURPOSE OF REVIEW To review existing mHealth-based interventions and examine their efficacy in reducing cardiovascular disease (CVD) risk factors. RECENT FINDINGS A total of 50 articles are included in this review. The majority of the mHealth interventions targeted a specific CVD risk factor, while 4 addressed 2 or more CVD risk factors. Of the 9 mHealth-supported weight loss intervention trials, 4 resulted in significant weight loss. Four out of 7 RCTs targeting improvement in physical activity reported significant improvement, while 4 of the 8 mHealth-supported smoking cessation intervention trials resulted in smoking abstinence. Of the 10 mHealth-based diabetes intervention trials, 5 reported significant reductions in HbA1c; however, only 3 out of the 9 antihypertension interventions resulted in significant reductions in blood pressure. There is a growing body of literature focused on mHealth interventions that address CVD risk factors. Despite the immense potential of mHealth interventions, evidence of their efficacy in mitigating cardiovascular risk is heterogeneous.
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Eberle C, Löhnert M, Stichling S. Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review. JMIR Mhealth Uhealth 2021; 9:e23477. [PMID: 33587045 PMCID: PMC7920757 DOI: 10.2196/23477] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 11/08/2020] [Accepted: 11/30/2020] [Indexed: 12/20/2022] Open
Abstract
Background According to the World Health Organization, the worldwide prevalence of diabetes mellitus (DM) is increasing dramatically and DM comprises a large part of the global burden of disease. At the same time, the ongoing digitalization that is occurring in society today offers novel possibilities to deal with this challenge, such as the creation of mobile health (mHealth) apps. However, while a great variety of DM-specific mHealth apps exist, the evidence in terms of their clinical effectiveness is still limited. Objective The objective of this review was to evaluate the clinical effectiveness of mHealth apps in DM management by analyzing health-related outcomes in patients diagnosed with type 1 DM (T1DM), type 2 DM (T2DM), and gestational DM. Methods A scoping review was performed. A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, EMBASE, CINAHL, and Web of Science Core Collection databases for studies published between January 2008 and October 2020. The studies were categorized by outcomes and type of DM. In addition, we carried out a meta-analysis to determine the impact of DM-specific mHealth apps on the management of glycated hemoglobin (HbA1c). Results In total, 27 studies comprising 2887 patients were included. We analyzed 19 randomized controlled trials, 1 randomized crossover trial, 1 exploratory study, 1 observational study, and 5 pre-post design studies. Overall, there was a clear improvement in HbA1c values in patients diagnosed with T1DM and T2DM. In addition, positive tendencies toward improved self-care and self-efficacy as a result of mHealth app use were found. The meta-analysis revealed an effect size, compared with usual care, of a mean difference of –0.54% (95% CI –0.8 to –0.28) for T2DM and –0.63% (95% CI –0.93 to –0.32) for T1DM. Conclusions DM-specific mHealth apps improved the glycemic control by significantly reducing HbA1c values in patients with T1DM and T2DM patients. In general, mHealth apps effectively enhanced DM management. However, further research in terms of clinical effectiveness needs to be done in greater detail.
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Affiliation(s)
- Claudia Eberle
- Medicine with Specialization in Internal Medicine and General Medicine, Hochschule Fulda-University of Applied Sciences, Fulda, Germany
| | - Maxine Löhnert
- Medicine with Specialization in Internal Medicine and General Medicine, Hochschule Fulda-University of Applied Sciences, Fulda, Germany
| | - Stefanie Stichling
- Medicine with Specialization in Internal Medicine and General Medicine, Hochschule Fulda-University of Applied Sciences, Fulda, Germany
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Xu Y, Xu L, Zhao W, Li Q, Li M, Lu W, Zeng H, Yan J, Yang D, Wu W, Weng J, Pan J, Liu F. Effectiveness of a WeChat Combined Continuous Flash Glucose Monitoring System on Glycemic Control in Juvenile Type 1 Diabetes Mellitus Management: Randomized Controlled Trial. Diabetes Metab Syndr Obes 2021; 14:1085-1094. [PMID: 33727842 PMCID: PMC7955684 DOI: 10.2147/dmso.s299070] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 02/23/2021] [Indexed: 12/12/2022] Open
Abstract
PURPOSE Smartphones have received increasing attention and achieved positive outcomes in diabetes intervention. The widespread use of WeChat in China provides an opportunity for self-management practices in patients with diabetes. Nevertheless, how to combine the strengths of the WeChat platform with traditional medical strategy remains to be explored. This study aimed to evaluate the efficacy of a novel flash glucose monitoring device combined with the WeChat platform in juvenile type 1 diabetes management. PATIENTS AND METHODS A total of 60 juvenile patients with type 1 diabetes were randomly assigned into three groups: a blood glucose self-monitoring group (group A), a flash glucose monitoring (group B), and a flash glucose monitoring combined WeChat-interactive management group (group C). The intergroup differences in demographics, biochemical indicators, and questionnaire scores of the Diabetes Monitoring and Treatment Satisfaction Questionnaire and Diabetes Specific Quality of Life assessment were compared at the baseline and after 6 months. RESULTS After the 6-month intervention, groups B and C showed significantly lower glycated hemoglobin A1c (HbA1c) levels compared to those observed at baseline (both P <0.05), with the largest decrease observed in group C (group B vs group C, P =0.04). Hypoglycemic episodes per month decreased from baseline in groups B and C (both P <0.05) and were more significant in group C (P <0.001). In addition, the DMTSQ scores increased in the 6th month in all groups (all P <0.05), and the largest rise in scores was found in group C, followed by groups B and A. The DQOL scores in groups B and C decreased significantly from the baseline (both P <0.05), with no change in group A. CONCLUSION Flash glucose monitoring combined with the WeChat-interactive system may help achieve sustained glycemic control and higher satisfaction in patients with juvenile type 1 diabetes. TRIAL REGISTRATION This study was registered at chictr.org.cn, number ChiCTR1900025495. Registered 29 August 2019.
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Affiliation(s)
- Yuejie Xu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China
| | - Lei Xu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China
| | - Weijing Zhao
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China
| | - Qing Li
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China
| | - Ming Li
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China
| | - Wei Lu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China
| | - Hui Zeng
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China
| | - Jinhua Yan
- Department of Endocrinology and Metabolic Disease, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China
| | - Daizhi Yang
- Department of Endocrinology and Metabolic Disease, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China
| | - Wei Wu
- Department of Pediatrics, Tongji Hospital, Wuhan Tongji Medical University, Wuhan, Hubei, 430030, People’s Republic of China
| | - Jianping Weng
- Department of Endocrinology and Metabolic Disease, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China
| | - Jiemin Pan
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China
- Correspondence: Jiemin Pan; Fang Liu Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 600 Yishan Road, Xuhui District, Shanghai, 200233, People’s Republic of ChinaTel +86-18930173803 Email ;
| | - Fang Liu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China
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20
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Hoque MR, Rahman MS, Nipa NJ, Hasan MR. Mobile health interventions in developing countries: A systematic review. Health Informatics J 2020; 26:2792-2810. [PMID: 32691659 DOI: 10.1177/1460458220937102] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
This study reviews the quality of evidence reported in mobile health intervention literature in the context of developing countries. A systematic search of renowned databases was conducted to find studies related to mobile health applications published between a period of 2013 and 2018. After a methodological screening, a total of 31 studies were included for data extraction and synthesis. The mobile health Evidence Reporting and Assessment checklist developed by the World Health Organization was then used to evaluate the rigor and completeness in evidence reporting. We report several important and interesting findings. First, there is a very low level of familiarity with the mobile health Evidence Reporting and Assessment checklist among the researchers and mobile health intervention designers from developing countries. Second, most studies do not adequately meet the essential criteria of evidence reporting mentioned in the mobile health Evidence Reporting and Assessment checklist. Third, there is a dearth of application of design science-based methods and theory-based frameworks in developing mobile health interventions. Fourth, most of the mobile health interventions are not ready for interoperability and to be integrated into the existing health information systems. Based on these findings, we recommend for robust and inclusive study plans to deliver highly evidence-based reports by mobile health intervention studies that are conducted in the context of developing countries.
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21
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Park SK, Bang CH, Lee SH. Evaluating the effect of a smartphone app-based self-management program for people with COPD: A randomized controlled trial. Appl Nurs Res 2020; 52:151231. [PMID: 31955942 DOI: 10.1016/j.apnr.2020.151231] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2019] [Revised: 09/07/2019] [Accepted: 01/05/2020] [Indexed: 01/24/2023]
Abstract
AIM To examine the effect of a 6-month, smartphone app-based self-management program for people with chronic obstructive pulmonary disease (COPD). BACKGROUND Technological interventions have been used for chronic disease management, but the effect of a self-management program using a smartphone app has not been evaluated in people with COPD. METHODS For this randomized controlled trial, patients with COPD (N = 44) were recruited in pulmonary medicine outpatient clinics at two, metropolitan, tertiary care, academic hospitals. Eligible participants were randomized into two groups and received group education and exercise sessions in the first month of the 6-month intervention. Participants in the experimental group received a smartphone app-based self-management program, which included education, exercises, self-monitoring of symptoms and exercise, and social support. Participants in the control group received one call a month from the research staff. Self-care behavior was measured as a primary outcome. All measures were administered at baseline and at 6 months. RESULTS After randomization, the experimental group numbered 22, the control group numbered 20, and 2 participants dropped out. Significant differences between groups were found in change score for self-care behavior, total activity count per wear time, and percent time spent in moderate-to-vigorous physical activity over 6 months. CONCLUSION A self-management program, using a smartphone app, can effect behavioral change in people with COPD. This program could be a boon to patients with COPD who have limited access to a health care provider, no opportunities for pulmonary rehabilitation, and frequent exacerbations.
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Affiliation(s)
| | - Cho Hee Bang
- School of Nursing, Ehwa Women's University, Seoul, Republic of Korea
| | - Seung Hyeun Lee
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Kyung Hee University School of Medicine, Republic of Korea
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22
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Zhang L, He X, Shen Y, Yu H, Pan J, Zhu W, Zhou J, Bao Y. Effectiveness of Smartphone App-Based Interactive Management on Glycemic Control in Chinese Patients With Poorly Controlled Diabetes: Randomized Controlled Trial. J Med Internet Res 2019; 21:e15401. [PMID: 31815677 PMCID: PMC6928697 DOI: 10.2196/15401] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2019] [Revised: 10/11/2019] [Accepted: 10/20/2019] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND In recent years, the rapid development of mobile medical technology has provided multiple ways for the long-term management of chronic diseases, especially diabetes. As a new type of management model, smartphone apps are global, convenient, cheap, and interactive. Although apps were proved to be more effective at glycemic control, compared with traditional computer- and Web-based telemedicine technologies, how to gain a further and sustained improvement is still being explored. OBJECTIVE The objective of this study was to investigate the effectiveness of an app-based interactive management model by a professional health care team on glycemic control in Chinese patients with poorly controlled diabetes. METHODS This study was a 6-month long, single-center, prospective randomized controlled trial. A total of 276 type 1 or type 2 diabetes patients were enrolled and randomized to the control group (group A), app self-management group (group B), and app interactive management group (group C) in a 1:1:1 ratio. The primary outcome was the change in glycated hemoglobin (HbA1c) level. Missing data were handled by multiple imputation. RESULTS At months 3 and 6, all 3 groups showed significant decreases in HbA1c levels (all P<.05). Patients in the app interactive management group had a significantly lower HbA1clevel than those in the app self-management group at 6 months (P=.04). The average HbA1c reduction in the app interactive management group was larger than that in the app self-management and control groups at both months 3 and 6 (all P<.05). However, no differences in HbA1c reduction were observed between the app self-management and control groups at both months 3 and 6 (both P>.05). Multivariate line regression analyses also showed that the app interactive management group was associated with the larger reduction of HbA1c compared with groups A and B at both months 3 and 6 (all P>.05). In addition, the app interactive management group had better control of triglyceride and high-density lipoprotein cholesterol levels at both months 3 and 6 compared with baseline (both P<.05). CONCLUSIONS In Chinese patients with poorly controlled diabetes, it was difficult to achieve long-term effective glucose improvement by using app self-management alone, but combining it with interactive management can help achieve rapid and sustained glycemic control. TRIAL REGISTRATION ClinicalTrials.gov NCT02589730; https://clinicaltrials.gov/ct2/show/NCT02589730.
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Affiliation(s)
- Lei Zhang
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Xingxing He
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yun Shen
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Haoyong Yu
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Jiemin Pan
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Wei Zhu
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Jian Zhou
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yuqian Bao
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
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23
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Yu Y, Yan Q, Li H, Li H, Wang L, Wang H, Zhang Y, Xu L, Tang Z, Yan X, Chen Y, He H, Chen J, Feng B. Effects of mobile phone application combined with or without self-monitoring of blood glucose on glycemic control in patients with diabetes: A randomized controlled trial. J Diabetes Investig 2019; 10:1365-1371. [PMID: 30815973 PMCID: PMC6717828 DOI: 10.1111/jdi.13031] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 02/14/2019] [Accepted: 02/25/2019] [Indexed: 12/29/2022] Open
Abstract
AIMS/INTRODUCTION There is potential for mobile applications to deliver new self-management interventions for chronic disease, especially in diabetes. The aim of the present study was to evaluate the effects of a mobile phone application (MPA) combined with or without self-monitoring of blood glucose (SMBG) on glycemic control in patients with diabetes. MATERIALS AND METHODS The study was a 24-week period, four-arm parallel group, non-blinded, randomized trial. A total of 185 patients with mean age of 52 years were randomized to group A (no MPA and no SMBG), group B (SMBG only), group C (MPA only) and group D (both MPA and SMBG were used). Changes in glycated hemoglobin (HbA1c), fasting plasma glucose and 1,5-anhydroglucitol from baseline to week 24 were analyzed. RESULTS At 24 weeks, the HbA1c levels in patients of all groups decreased significantly from baseline. There were significant differences in the proportions of patients that achieved HbA1c <7% between groups, especially in group C and group D, compared with group A at week 24 (60.4%, 62.2% vs 25.5%, all P < 0.05). 1,5-Anhydroglucitol changes were obvious in group A and group C at week 24 from baseline (all P < 0.05 within groups). Factorial analysis of anova showed that MPA intervention was the main effective factor for HbA1c change (F = 4.59, P = 0.034), and there was no effect on HbA1c change for SMBG intervention (P = 0.975). CONCLUSIONS Implementation of the MPA, Diabetes-Carer, is effective in improving the proportion of HbA1c <7% in patients with type 2 diabetes.
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Affiliation(s)
- Yuan Yu
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Qun Yan
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Huizhi Li
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Hongmei Li
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Lin Wang
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Hua Wang
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Yiyun Zhang
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Lei Xu
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Zhaosheng Tang
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Xinfeng Yan
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Yinghua Chen
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Huili He
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Jie Chen
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
| | - Bo Feng
- Department of EndocrinologyShanghai East HospitalTongji University School of MedicineShanghaiChina
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