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Trial Design
This controlled clinical trial study involved 60 patients admitted to the Ghaem Hospital of Mashhad, Iran. These patients were specifically from the cardiac surgery intensive care unit and were admitted between May 2020 and January 2021 (Fig. 1).
CONSORT Flow Chart of participants
Participants
The study included patients who met specific inclusion criteria. These criteria required the patients to be between the ages of 18 and 60 and willing to undergo non-emergency coronary artery graft surgery. On the other hand, exclusion criteria included patients who experienced loss of consciousness until the day following surgery, those who did not have a smartphone, individuals with severe postoperative arrhythmias and hemodynamic disorders, and patients who were prohibited by their doctor from participating in rehabilitation.
Intervention
Software production
Prior to the software’s design, extensive research was conducted to prepare its content. This involved reviewing various texts, including articles, reference books, and gathering insights from experienced nurses in specialized care units. The content was then submitted to a panel of 10 specialists for validation, and their suggested revisions were incorporated.
The educational content of the software covered a range of topics, including respiratory diaphragmatic exercises, instructions on physical exercises and their proper execution, discussions and interactions with patients, and encouragement for patients to engage in routine activities. These concepts were primarily presented through instructional videos and engaging animations.
Once the content was finalized, it was handed over to the software development and information technology team for the creation of the software. After the initial software was developed, a specialized validation process was conducted by 10 IT experts to ensure its functionality and effectiveness.
To validate the software, both white-box and black-box testing methods were employed. In black-box testing, users with no knowledge of the software’s internal structure input their desired items and verify the recorded information. The aim is to ensure accurate data recording. White-box testing, on the other hand, requires users to have knowledge of the software’s internal structure and is typically executed by designers or experts. For instance, to assess the software’s speed, various items were selected at different speeds, and the accuracy of the selections was examined.
The next phase involved compatibility testing and security testing. Compatibility testing involved installing the application on multiple Android-based smartphones and tablets to assess its performance on each device. In security testing, a double confirmation method was implemented to ensure accurate recording of each patient’s issues. This involved the patient confirming their selected item by clicking again, reducing the possibility of accidental data entry errors.
The augmented reality software was registered and approved within the electronic services system of the Information Technology Organization of Iran.
To evaluate patient satisfaction with the augmented reality software, the Mobile Application Rating Scale (MARS) was employed.
This scale evaluates the application’s quality and performance across four dimensions: attractiveness (5 questions), functionality (4 questions), aesthetics (3 questions), information (7 questions), and subjective quality (4 questions). Each item in the scale was rated on a 5-point scale. The maximum achievable score was 115, while the minimum acceptable score was set at 23. For a detailed presentation of the results, please refer to (Table 1).
Phase I cardiac rehabilitation training based on augmented reality
After establishing the necessary agreements with officials at Ghaem Hospital in Mashhad, Iran, the first author of the study initiated the sampling process. In the intervention group, the rehabilitation program training started upon the patient’s entry into the cardiac surgery intensive care unit and continued until their discharge from the unit.
During multiple sessions, augmented reality software was utilized to train patients in physical activities, such as walking around the inpatient ward and climbing stairs. These exercises were done under the direct supervision of the researcher and were individually taught to each patient using the augmented reality software. The duration of physical activity varied based on the patient’s condition and length of hospital stay, ranging from 5 to 10 min. Throughout the rehabilitation sessions, ECG and the perceived exercise intensity were closely monitored and controlled.
In the control group, the rehabilitation training program was implemented using a routine method based on the Ministry of Health protocol. The researcher provided face-to-face training within the unit. Both the intervention and control groups completed the cardiac self-efficacy questionnaire upon admission and at the time of discharge in the special care unit of cardiac surgery.
Outcomes
In the data collection process, two demographic information questionnaires and a cardiac self-efficacy questionnaire were utilized.
The cardiac self-efficacy questionnaire used in this study was the Cardiovascular Management Self-Efficacy Questionnaire, which was developed by Estka from Italy in 2015. This questionnaire consists of 9 questions, each rated on a 5-point Likert scale, ranging from “completely confident” to “not at all confident.” The questionnaire is composed of three subscales.
The first four questions assess a person’s belief in their ability to quit smoking, maintain proper nutrition, engage in exercise, and avoid stressful situations. This subscale is referred to as self-efficacy of cardiac risk factors. Questions 5 and 6 pertain to a person’s confidence in remembering to take medications correctly, representing self-efficacy of treatment adherence. Lastly, questions 7–9 evaluate a person’s belief in their ability to identify symptoms and signs of disease exacerbation, indicating self-efficacy in symptom recognition.
Each response is assigned a score, with “not confident at all” receiving a score of one, “slightly confident” receiving a score of two, “somewhat confident” receiving a score of three, “fairly confident” receiving a score of four, and “completely confident” receiving a score of five. The total scores range from 9 to 45, with higher scores indicating greater self-efficacy in cardiovascular management [21]. Borzou et al. (2017) evaluated the validity and reliability of this tool in Iran [33]. The patients completed the Cardiovascular Management Self-Efficacy Questionnaire both before and after the intervention.
Sample size and randomization
The study involved the continuous and purposeful selection of patients who were then randomly assigned to one of two groups. After confirming that they met the inclusion criteria, eligible individuals were divided into intervention and control groups using a random sequence generated by SPSS software. This sequence was kept in a sealed envelope to maintain confidentiality. While it was challenging to blind the participants in this trial, the outcome assessors and statisticians were unaware of the type of intervention, ensuring a level of objectivity.
Since no similar study was found that examined the efficacy of phase I cardiac rehabilitation training based on augmented reality on the self-efficacy of patients undergoing coronary artery bypass graft surgery, a sample size of 10 participants was determined for each group. The sample size was calculated using the mean comparison formula, with a confidence interval of 95% and a test power of 80% for each group, resulting in a total of 20 participants. To account for potential dropout probability, an additional 30 participants were added to each group, representing a 10% increase from the calculated values in the formula.
$$N = {\text{ }}\left( {Z1 – \alpha /2{\text{ }} + {\text{ }}Z1 – \beta } \right)2{\text{ }}\left( {S12{\text{ }} + {\text{ }}S22} \right)/\left( {X1 – X2} \right)2$$
$${Z_{1 – \alpha /2}} = {\text{ }}196$$
$${Z_{1 – \beta }} = {\text{ }}0.85$$
$${X_2} = {\text{ }}8.3$$
Statistical methods
After data collection and sampling, the collected data were analyzed using SPSS 21. Various statistical tests were employed, including independent t-test, Mann-Whitney test, paired t-test, and chi-square test. These tests were conducted with a 95% confidence level to ensure statistical significance. Descriptive indicators such as mean, standard deviation, and frequency were also used to provide a comprehensive overview of the data. Cohen’s d was also used to evaluate the magnitude of the effect size, calculated by standardized mean difference, with g > 0.2 to 0.5 = small effect size, g > 0.5 to 0.8 = medium effect size and g > 0.8 = large effect size [38].
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