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Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach
BACKGROUND: Diabetes is a significant public health issue. Saudi Arabia has the highest prevalence of type 2 diabetes mellitus (T2DM) in the Arab world. Currently, it affects 31.6% of the general population, and the prevalence of T2DM is predicted to rise to 45.36% by 2030. Mobile health (mHealth) o...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7519429/ https://www.ncbi.nlm.nih.gov/pubmed/32678798 http://dx.doi.org/10.2196/17083 |
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author | Alenazi, Hanan A Jamal, Amr Batais, Mohammed A |
author_facet | Alenazi, Hanan A Jamal, Amr Batais, Mohammed A |
author_sort | Alenazi, Hanan A |
collection | PubMed |
description | BACKGROUND: Diabetes is a significant public health issue. Saudi Arabia has the highest prevalence of type 2 diabetes mellitus (T2DM) in the Arab world. Currently, it affects 31.6% of the general population, and the prevalence of T2DM is predicted to rise to 45.36% by 2030. Mobile health (mHealth) offers improved and cost-effective care to people with T2DM. However, the efficiency of engagement strategies and features of this technology need to be reviewed and standardized according to stakeholder and expert perspectives. OBJECTIVE: The main objective of this study was to identify the most agreed-upon features for T2DM self-management mobile apps; the secondary objective was to identify the most agreed-upon strategies that prompt users to use these apps. METHODS: In this study, a 4-round modified Delphi method was applied by experts in the domain of diabetes care. RESULTS: In total, 11 experts with a mean age of 47.09 years (SD 11.70) consented to participate in the study. Overall, 36 app features were generated. The group of experts displayed weak agreement in their ranking of intervention components (Kendall W=0.275; P<.001). The top 5 features included insulin dose adjustment according to carbohydrate counting and blood glucose readings (5.36), alerting a caregiver of abnormal or critical readings (6.09), nutrition education (12.45), contacts for guidance if required (12.64), and offering patient-specific education tailored to the user’s goals, needs, and blood glucose readings (12.90). In total, 21 engagement strategies were generated. Overall, the experts showed a moderate degree of consensus in their strategy rankings (Kendall W=0.454; P<.001). The top 5 engagement strategies included a user-friendly design (educational and age-appropriate design; 2.82), a free app (3.73), allowing the user to communicate or send information/data to a health care provider (HCP; 5.36), HCPs prescribing the mobile app in the clinic and asking about patients’ app use compliance during clinical visits (6.91), and flexibility and customization (7.91). CONCLUSIONS: This is the first study in the region consisting of a local panel of experts from the diabetes field gathering together. We used an iterative process to combine the experts’ opinions into a group consensus. The results of this study could thus be useful for health app developers and HCPs and inform future decision making on the topic. |
format | Online Article Text |
id | pubmed-7519429 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-75194292020-10-09 Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach Alenazi, Hanan A Jamal, Amr Batais, Mohammed A JMIR Mhealth Uhealth Original Paper BACKGROUND: Diabetes is a significant public health issue. Saudi Arabia has the highest prevalence of type 2 diabetes mellitus (T2DM) in the Arab world. Currently, it affects 31.6% of the general population, and the prevalence of T2DM is predicted to rise to 45.36% by 2030. Mobile health (mHealth) offers improved and cost-effective care to people with T2DM. However, the efficiency of engagement strategies and features of this technology need to be reviewed and standardized according to stakeholder and expert perspectives. OBJECTIVE: The main objective of this study was to identify the most agreed-upon features for T2DM self-management mobile apps; the secondary objective was to identify the most agreed-upon strategies that prompt users to use these apps. METHODS: In this study, a 4-round modified Delphi method was applied by experts in the domain of diabetes care. RESULTS: In total, 11 experts with a mean age of 47.09 years (SD 11.70) consented to participate in the study. Overall, 36 app features were generated. The group of experts displayed weak agreement in their ranking of intervention components (Kendall W=0.275; P<.001). The top 5 features included insulin dose adjustment according to carbohydrate counting and blood glucose readings (5.36), alerting a caregiver of abnormal or critical readings (6.09), nutrition education (12.45), contacts for guidance if required (12.64), and offering patient-specific education tailored to the user’s goals, needs, and blood glucose readings (12.90). In total, 21 engagement strategies were generated. Overall, the experts showed a moderate degree of consensus in their strategy rankings (Kendall W=0.454; P<.001). The top 5 engagement strategies included a user-friendly design (educational and age-appropriate design; 2.82), a free app (3.73), allowing the user to communicate or send information/data to a health care provider (HCP; 5.36), HCPs prescribing the mobile app in the clinic and asking about patients’ app use compliance during clinical visits (6.91), and flexibility and customization (7.91). CONCLUSIONS: This is the first study in the region consisting of a local panel of experts from the diabetes field gathering together. We used an iterative process to combine the experts’ opinions into a group consensus. The results of this study could thus be useful for health app developers and HCPs and inform future decision making on the topic. JMIR Publications 2020-09-11 /pmc/articles/PMC7519429/ /pubmed/32678798 http://dx.doi.org/10.2196/17083 Text en ©Hanan A Alenazi, Amr Jamal, Mohammed A Batais. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 11.09.2020. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Alenazi, Hanan A Jamal, Amr Batais, Mohammed A Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach |
title | Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach |
title_full | Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach |
title_fullStr | Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach |
title_full_unstemmed | Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach |
title_short | Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach |
title_sort | identification of type 2 diabetes management mobile app features and engagement strategies: modified delphi approach |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7519429/ https://www.ncbi.nlm.nih.gov/pubmed/32678798 http://dx.doi.org/10.2196/17083 |
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