Effects of an Animated Mobile Application on Diabetic Foot Ulcer Management
- Conditions
- Diabetic Foot Ulcers (DFU)
- Registration Number
- NCT06977048
- Lead Sponsor
- Saglik Bilimleri Universitesi
- Brief Summary
This study was designed to evaluate the effect of education delivered through an animation-based mobile application on the knowledge level, self-efficacy, wound size, and metabolic parameters of individuals with diabetic foot ulcers.
- Detailed Description
Diabetic foot is one of the most serious complications of diabetes, negatively affecting not only patients but also caregivers, healthcare professionals, and the broader society, both medically and economically. Peripheral neuropathy, peripheral arterial disease, microvascular and macrovascular alterations, impaired glycemic regulation, recurrent trauma, and inadequate foot care can lead to the development of diabetic foot ulcers (DFUs), which may progress to osteomyelitis. Each year, approximately 18.6 million people worldwide are affected by diabetic foot ulcers. The five-year mortality rate among these individuals is around 30%, and it exceeds 70% in those with a history of major amputation. Primary treatment approaches for DFUs include surgical debridement, offloading, treatment of peripheral arterial disease, and infection management. Additionally, therapies such as hyperbaric oxygen, wound dressings, negative pressure wound therapy, and topical oxygen are also employed in the management of diabetic foot ulcers. Compared to amputations due to other causes, a significant proportion of amputations resulting from DFUs are preventable. For this reason, education on diabetes and foot care has been shown to prevent ulcer formation and subsequently reduce amputation rates and associated morbidity.
Individuals with diabetes need to possess an adequate level of self-efficacy in order to effectively manage lifelong treatment, care, and lifestyle changes. Self-efficacy is defined as a cognitive process through which individuals believe they can influence future outcomes via environmental and social factors and thereby learn new behaviors. It is known that individuals with high self-efficacy are more actively involved in their own care and experience the chronic disease process more successfully. In diabetes management, perceived self-efficacy is considered crucial by researchers and clinicians, as it is associated with adopting a healthy lifestyle, adhering to medication and treatment regimens, and managing stress. Assessing and promoting patients' self-efficacy is a valuable tool in healthcare settings as it enhances motivation for self-care. Supporting patients in this regard may increase life expectancy and help regulate health behaviors. In a study by Bahador et al., a three-month education program for patients with diabetic foot ulcers significantly improved self-efficacy, foot ulcer care rates, and reduced re-ulceration and complication rates. Similarly, Ayaz, Dinçer, and Oğuz (2020) reviewed 26 systematic studies and 8 meta-analyses on the effects of foot care education in diabetic patients and found that such education improved patients' knowledge and behaviors. The authors emphasized the need for long-term educational interventions.
Recent advances in technology and healthcare worldwide have fostered the integration of these two fields and brought mobile health applications to the forefront. Mobile health applications are software tools used via mobile devices such as smartphones or tablets, and they offer advantages over traditional methods. These applications are employed in the management of various chronic diseases including chronic obstructive pulmonary disease (COPD), depression, dementia, and diabetes, particularly for medication adherence, rehabilitation, symptom control, and tracking medical records. In a study by Marquen et al., a mobile application combined with nursing consultation improved foot self-care among individuals with type 2 diabetes. Similarly, Kilic and Karadag developed a Mobile Diabetic Foot Self-Care System for patients with diabetes mellitus, which enhanced patients' knowledge, behaviors, and self-efficacy scores. The use of mobile applications plays a significant role in advancing mobile health technologies, and it is important that such applications are supported by daily messages, videos, and animations.
Animation is a form of educational material that uses visual simulations to present theoretical knowledge in a more accessible format. Through animation videos, key points of a topic can be highlighted to improve patient understanding, allow repeated viewing of the material, and enhance knowledge levels. In a study by Alyami et al., visual animations shown to patients with type 2 diabetes, their caregivers, and healthcare professionals were found to improve patients' perceptions and enhance the effectiveness of diabetes education. Likewise, Maisrikrod et al. developed an animated educational tool aimed at increasing community awareness in tropical regions where melioidosis and diabetes are prevalent. They concluded that such tools can serve as low-cost, adaptable health education materials.
Recruitment & Eligibility
- Status
- ACTIVE_NOT_RECRUITING
- Sex
- All
- Target Recruitment
- 74
- Having a diagnosis of diabetic foot ulcer, having stage 1-2 diabetic foot ulcer according to Wagner classification system, being between the ages of 18-65, being literate, having and using a mobile phone with IOS and ANDROID operating system, volunteering to participate in the study
- Users who want to withdraw from the research, the patient's exitus during the research process, users who do not log in to the mobile application once a week during the implementation process of the research (twelve weeks) will be excluded from the research.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Primary Outcome Measures
Name Time Method Change in Diabetic Foot Ulcer Size (cm²) aseline (Week 0) Follow-up (Week 12) (Optional intermediate check at Week 8) This outcome measures the change in the surface area (cm²) of the diabetic foot ulcer from baseline (Week 0) to the end of the intervention (Week 12). The wound size is calculated using the formula length × width (cm × cm).
The Diabetic Foot Care Self-Efficacy Scale (DFCSES) Baseline (Week 0) Follow-up (Week 12) The Diabetic Foot Care Self-Efficacy Scale (DFCSES), originally developed by Quarles (2005) and adapted into Turkish by Kır Biçer (2011), will be used to assess participants' self-efficacy regarding diabetic foot care. The scale consists of 9 items rated on a scale from 0 (not confident at all) to 10 (completely confident), with total scores ranging from 0 to 90. Higher scores reflect greater self-efficacy in diabetic foot care. The change in total score from baseline to 12 weeks post-intervention will be evaluated.
Change in Diabetic Foot Knowledge Score Baseline (Week 0) Follow-up (Week 12) Knowledge of diabetic foot care will be measured using a 5-item subscale from the Diabetes Knowledge Questionnaire-24 (DKQ-24), originally developed by Garcia et al. and adapted into Turkish by Biçer. Each item is answered as "Yes," "No," or "I don't know." Total scores range from 0 to 5, with higher scores reflecting greater knowledge of diabetic foot care. The change in score from baseline to 12 weeks post-intervention will be assessed.
- Secondary Outcome Measures
Name Time Method Change in HDL Cholesterol (mg/dL) Baseline (Week 0) Follow-up (Week 12) HDL levels (mg/dL) will be obtained from standard lab testing. The difference between pre- and post-intervention values will be evaluated.
Change in LDL Cholesterol (mg/dL) Baseline (Week 0) Follow-up (Week 12) LDL cholesterol levels (mg/dL) will be retrieved from routine blood tests. Change from baseline to follow-up will be measured.
Change in Total Cholesterol (mg/dL) Baseline (Week 0) Follow-up (Week 12) Total cholesterol levels (mg/dL) will be taken from regular lab reports. Change from baseline to 12 weeks will be analyzed.
Change in Body Mass Index (BMI, kg/m²) Baseline (Week 0) Follow-up (Week 12) BMI will be calculated from measured height and weight. The change in BMI (kg/m²) from baseline to 12 weeks post-intervention will be recorded.
Change in HbA1c (%) Baseline (Week 0) Follow-up (Week 12) HbA1c levels will be measured as part of routine laboratory testing. The change in HbA1c (%) from baseline to 12 weeks after the intervention will be evaluated.
Change in Fasting Blood Glucose (mg/dL) Baseline (Week 0) Follow-up (Week 12) Fasting blood glucose (mg/dL) levels will be obtained from routine clinical tests. The change between baseline and 12 weeks post-intervention will be assessed.
Change in Triglycerides (mg/dL) Baseline (Week 0) Follow-up (Week 12) Serum triglyceride levels (mg/dL) will be recorded from routine lab results. The change from baseline to 12 weeks will be analyzed.
Trial Locations
- Locations (1)
Gülhane Training and Research Hospital, University of Health Sciences, Turkey
🇹🇷Ankara, Keçiören, Turkey