Setting and Study Design:
This quasi-experimental study with a pretest-posttest design was conducted on two groups. Seventy elderly individuals with chronic illnesses (diabetes, cardiovascular, or kidney disease) who referred to teaching hospitals in Zahedan were selected based on the sample size formula and similar studies(16), and were randomly assigned to intervention and control groups (35 participants each).
The focus on elderly individuals with chronic diseases was grounded in compelling scientific, epidemiological, and theoretical reasons. The higher prevalence of chronic conditions and polypharmacy in this age group, along with the progressive decline in functional and cognitive capacities associated with aging, puts them at greater risk of inadequate self-care and, consequently, reduced quality of life.

Population, Inclusion, and Exclusion Criteria:
Inclusion criteria were: age over 65 years, basic literacy (reading and writing), owning and being able to use a smartphone, having at least one of the mentioned chronic diseases for a minimum of six months, and willingness to participate in the study. Exclusion criteria included not using the software for more than one week, death, or sudden deterioration in physical condition.
Data Collection Tool:
Data collection tools consisted of two parts: a demographic information form and the World Health Organization Quality of Life (WHOQOL) questionnaire, which includes four subscales—physical health, psychological health, social relationships, and environmental health—along with a general quality of life score. Raw scores for each subscale were converted into standardized scores (0 to 100) using a specific formula, with higher scores indicating better quality of life. The validity and reliability of this questionnaire have been confirmed in Iran by Nasiri et al., reporting a Cronbach’s alpha coefficient of 0.84 (17, 18).
Study Procedure:
To conduct the study, the researcher was present at the study site, introduced themselves, and provided a complete explanation of the study. Informed written consent was obtained from eligible participants. Participants were assured that their information would remain confidential and that they could withdraw from the study at any time.
Initially, the educational needs of elderly participants in the intervention group were assessed using a needs assessment worksheet based on Orem’s self-care model, adapted from the book Concepts and Theories in Nursing by Amirkhanyan(19).The study was implemented by sending the intervention group a link to the educational software developed by the researchers. The software was designed and implemented by a technology company located in the Science and Technology Park of Zahedan University of Medical Sciences. This company has a proven track record in developing digital health solutions and holds valid certifications in medical software development.
The software was based on Orem’s theory with a disease-centered approach, containing three dedicated modules (diabetes, hypertension, and kidney disease) alongside shared content grounded in Orem’s model. Upon logging in with a unique code, each user was directed only to the module corresponding to their specific condition, with no access to the other modules.
The educational content of each module is presented (Table 1). The Orem-based core, serving as the theoretical foundation across all modules, operationalized the three major components of Orem’s theory through practical tools. For universal self-care needs, training was provided in areas such as nutrition, sleep management, and fall prevention. For developmental needs, content included strategies for reducing anxiety and maintaining cognitive function. For health deviation needs, topics included polypharmacy management and monitoring of warning signs.
The intervention group used the software for two months. Concurrently, the researcher conducted structured follow-up phone calls twice a week (a total of 16 calls, each lasting 15–20 minutes per participant). These calls were made by the corresponding author and aimed to resolve technical issues with the software, respond to content-related questions about self-care, and gather user feedback for system improvement. This interactive approach was integrated with the software’s automatic monitoring features (tracking usage time and educational progress) to ensure the intervention was delivered optimally and with maximum effectiveness.
Two months after the intervention, both the intervention and control groups completed the quality of life questionnaire again.
Table 1
Educational Content by Disease Module
Educational Content | Disease Module |
|---|
Visual instruction on using a glucometer Smart logging of results with weekly trend charts Automatic alerts for high/low blood sugar levels Foot examination training Step-by-step visual guide for daily foot washing and inspection Food image bank categorized by glycemic index (green, yellow, red) Carbohydrate calculator via product barcode scanning Audio guide for managing hypoglycemic episodes Visual checklist of diabetic ketoacidosis symptoms | Diabetes Module |
Instruction on calibrating home blood pressure monitors Guided breathing exercises with audio support Digital diary for recording stress triggers Short games to reduce anxiety Barcode scanning of food items to display sodium content Weekly low-sodium meal plans with quick recipes Warning signs of stroke | Hypertension Module |
Smart fluid intake calculator Image gallery of high-potassium/phosphorus foods with warning labels Visual checklist for detecting edema Instruction on daily weight monitoring Medication alerts to avoid NSAIDs | Kidney Disease Module |
Statistical Analysis:
After data collection, normality was assessed using the Shapiro-Wilk test. Subsequently, the data were analyzed using descriptive and inferential statistics. Paired t-tests were used for within-group comparisons, independent t-tests for between-group comparisons of variables, and Chi-square and Fisher’s exact tests for categorical data. All analyses were conducted using SPSS version 27, and a significance level of 0.05 was considered.