Digital Healthcare Intervention to Improve Self-Management for Patients with Type 2 Diabetes: A Scoping Review

Villalobos, Nadia; Vela, Francisco Serna; Hernandez, Luis Morales

doi:10.29024/jsim.78

Cited by 13 publications

(13 citation statements)

References 30 publications

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“…A consistent finding in the present study was that the use of MyFood motivated the majority of the patients to reach their nutritional targets. This corresponds with results from a recent scoping review of the use of eHealth systems to patients with type 2 diabetes, where the eHealth systems contributed to increased motivation, awareness and change of habits to follow the allocated treatment [38]. The possibility to keep track of nutrition was also found to motivate the patients in a Danish qualitative study of hospitalized patients' experiences of being undernourished [39] and in an Australian study describing patients' perceptions [35] and hospital staff's perceptions [40] of an electronic program to engage patients in nutrition care bedside.…”

Section: Patient Empowermentsupporting

confidence: 82%

Process evaluation of the implementation of a decision support system to prevent and treat disease-related malnutrition in a hospital setting

Paulsen

Varsi

Andersen

2021

BMC Health Serv Res

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Background Malnutrition is present in 30% of hospitalized patients and has adverse outcomes for the patient and the healthcare system. The current practice for nutritional care is associated with many barriers. The MyFood decision support system was developed to prevent and treat malnutrition. Methods This paper reports on a process evaluation that was completed within an effectiveness trial. MyFood is a digital tool with an interface consisting of an app and a website. MyFood includes functions to record and evaluate dietary intake. It also provides reports to nurses, including tailored recommendations for nutritional treatment. We used an effectiveness-implementation hybrid design in a randomized controlled trial. The RE-AIM (Reach, Efficiency, Adoption, Implementation, Maintenance) framework was used to perform a process evaluation alongside the randomized controlled trial, using a combination of quantitative and qualitative methods. An implementation plan, including implementation strategies, was developed to plan and guide the study. Results Reach: In total, 88% of eligible patients consented to participate (n = 100). Adoption: Approximately 75% of the nurses signed up to use MyFood and 50% used the reports. Implementation: MyFood empowered the patients in their nutritional situation and acted as a motivation to eat to reach their nutritional target. The compliance of using MyFood was higher among the patients than the nurses. A barrier for use of MyFood among the nurses was different digital systems which were not integrated and the log-in procedure to the MyFood website. Despite limited use by some nurses, the majority of the nurses claimed that MyFood was useful, better than the current practice, and should be implemented in the healthcare system. Conclusions This study used a process evaluation to interpret the results of a randomized controlled trial more in-depth. The patients were highly compliant, however, the compliance was lower among the nurses. MyFood empowered the patients in their nutritional situation, the usability was considered as high, and the experiences and attitudes towards MyFood were primarily positive. Focus on strategies to improve the nurses’ compliance may in the future improve the MyFood system’s potential. Trial registration The trial was registered in ClinicalTrials.gov 26/01/2018 (NCT03412695).

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Section: Patient Empowermentsupporting

confidence: 82%

Process evaluation of the implementation of a decision support system to prevent and treat disease-related malnutrition in a hospital setting

Paulsen

Varsi

Andersen

2021

BMC Health Serv Res

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“…This encapsulates the lack of motivation and engagement in mHealth interventions that is further aggravated by the lack of face‐to‐face interactions with health professionals to upkeep treatment adherence. 52 It is therefore important to factor in patients' adherence level when considering the effectiveness of mHealth interventions. Above all, the development of mHealth interventions against chronic diseases is still in the infancy stage given its recency of implementation, even in the context of diabetes.…”

Section: Discussionmentioning

confidence: 99%

Effects of mobile health interventions on health‐related outcomes in older adults with type 2 diabetes: A systematic review and meta‐analysis

Lee

Aziz

Chan

et al. 2023

Journal of Diabetes

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Background Type 2 diabetes mellitus (T2DM) is a chronic metabolic condition that is associated with multiple comorbidities. Apart from pharmacological approaches, patient self‐management remains the gold standard of care for diabetes. Improving patients' self‐management among the elderly with mobile health (mHealth) interventions is critical, especially in times of the COVID‐19 pandemic. However, the extent of mHealth efficacy in managing T2DM in the older population remains unknown. Hence, the present review examined the effectiveness of mHealth interventions on cardiometabolic outcomes in older adults with T2DM. Methods A systematic search from the inception till May 31, 2021, in the MEDLINE, Embase, and PubMed databases was conducted, and 16 randomized controlled trials were included in the analysis. Results The results showed significant benefits on glycosylated hemoglobin (HbA1c) (mean difference −0.24%; 95% confidence interval [CI]: −0.44, −0.05; p = 0.01), postprandial blood glucose (−2.91 mmol/L; 95% CI: −4.78, −1.03; p = 0.002), and triglycerides (−0.09 mmol/L; 95% CI: −0.17, −0.02; p = 0.010), but not on low‐density lipoprotein cholesterol (−0.06 mmol/L; 95% CI: −0.14, 0.02; p = 0.170), high‐density lipoprotein cholesterol (0.05 mmol/L; 95% CI: −0.03, 0.13; p = 0.220), and blood pressure (systolic blood pressure −0.82 mm Hg; 95% CI: −4.65, 3.00; p = 0.670; diastolic blood pressure −1.71 mmHg; 95% CI: −3.71, 0.29; p = 0.090). Conclusions Among older adults with T2DM, mHealth interventions were associated with improved cardiometabolic outcomes versus usual care. Its efficacy can be improved in the future as the current stage of mHealth development is at its infancy. Addressing barriers such as technological frustrations may help strategize approaches to further increase the uptake and efficacy of mHealth interventions among older adults with T2DM.

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“…Direct access to the health information on the Internet or to smartphone apps can help people to interpret symptoms, to anticipate diagnosis, deal with complaints, and thus self-manage the behavior related to health or to disease. Most e-Health applications are designed to raise awareness among people with a specific condition, track related health data, and stimulate self-care behavior [41]. Apps influencing specific behavior often do so in the short term.…”

Section: The Relationship Between Patient-directed E-health Tools And...mentioning

confidence: 99%

The Promise of Digital Self-Management: A Reflection about the Effects of Patient-Targeted e-Health Tools on Self-Management and Wellbeing

Olmen

2022

IJERPH

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Increasingly, people have direct access to e-Health resources such as health information on the Internet, personal health portals, and wearable self-management applications, which have the potential to reinforce the simultaneously growing focus on self-management and wellbeing. To examine these relationships, we searched using keywords self-management, patient-targeting e-Health tools, and health as wellbeing. Direct access to the health information on the Internet or diagnostic apps on a smartphone can help people to self-manage health issues, but also leads to uncertainty, stress, and avoidance. Uncertainties relate to the quality of information and to use and misuse of information. Most self-management support programs focus on medical management. The relationship between self-management and wellbeing is not straightforward. While the influence of stress and negative social emotions on self-management is recognized as an important cause of the negative spiral, empirical research on this topic is limited to health literacy studies. Evidence on health apps showed positive effects on specific actions and symptoms and potential for increasing awareness and ownership by people. Effects on more complex behaviors such as participation cannot be established. This review discovers relatively unknown and understudied angles and perspectives about the relationship between e-Health, self-management, and wellbeing.

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Digital Healthcare Intervention to Improve Self-Management for Patients with Type 2 Diabetes: A Scoping Review

Cited by 13 publications

References 30 publications

Process evaluation of the implementation of a decision support system to prevent and treat disease-related malnutrition in a hospital setting

Process evaluation of the implementation of a decision support system to prevent and treat disease-related malnutrition in a hospital setting

Effects of mobile health interventions on health‐related outcomes in older adults with type 2 diabetes: A systematic review and meta‐analysis

The Promise of Digital Self-Management: A Reflection about the Effects of Patient-Targeted e-Health Tools on Self-Management and Wellbeing

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