Introduction 
Chronic diseases or non-communicable diseases (NCDs) are considered an invisible epidemic that jeopardizes the future of global health by the World Health Organization (WHO) (Dadgar & Joshi, 2018). NCDs take the lives of 41 million people annually, which is equivalent to 74% of all deaths globally (WHO, 2022). The increasing prevalence of chronic diseases has brought challenges for patients, healthcare providers, and global society. As technology evolves, healthcare providers are looking for innovative solutions to address these challenges (Zare & Jebraeily, 2018). Using information and communication technology (ICT) is an opportunity for patients and their families to improve the quality, access, and efficacy of healthcare (Kumar et al., 2022). The extensive use of ICT to provide healthcare facilitates access to health-related information even for patients living in remote areas (Afshar et al., 2014; Al-Shorbaji, 2021; Antoun, 2016). 
ICT refers to technology that provides access to information and communication through a wide range of communication tools (Kaware & Sain, 2015). In the present study, ICT means access to this technology through various devices, such as computers, laptops, the Internet, and smartphones. WHO defines eHealth as the cost-effective and safe use of ICT in health support and health-related fields, including healthcare services, health surveillance, health literature, and health education, knowledge, and research (WHO, eHealth). Although technological advances in eHealth improve self-management and disease control and reduce costs, patients often avoid using these advances, perhaps because they are often overlooked in the design of these technologies (Dodgar & Joshi, 2018), they are inadequate familiar with them, or their access is limited (Izadi-Avanji et al., 2022; Yazdani-Darki et al., 2020). According to WHO, the Eastern Mediterranean region consists of different levels of maturity and readiness to use eHealth as a key element in the delivery of health care services (WHO, eHealth).
According to a study in the United States, although the benefits of using ICT were numerous, doctors rarely used technologies, such as e-mail, to communicate with patients, and most patients were dissatisfied (Antoun, 2016). In Iran, the use of ICT in health is not as much as in developed countries (Farahmandian et al., 2015). Physical and mental limitations, the lack of proper knowledge and awareness, limited access to technology, and unfavorable attitudes toward technology are among the factors that have reduced its use (Yazdani-Darki et al., 2020). Considering the ever-increasing growth of information and communication technology and the importance of its use in the health sector, it is necessary to evaluate the use of technology in different populations, especially chronic diseases, to facilitate the formulation of strategic and operational plans and the allocation of realistic resources in this field (Hemmat et al., 2019). To help manage chronic diseases using ICT, it seems necessary to have a comprehensive tool that is developed based on the direct experience of patients (Ekeland et al., 2010). Based on the available contents of national and international electronic scientific databases, no comprehensive tool has yet been designed to measure the use of ICT among patients with chronic diseases. Most of the existing designed tools are related to the use of ICT in the field of education (Odhiambo & Onyango, 2015; Torres et al., 2013). The instruments to measure which kind of ICTs are available to patients and how patients use them are yet to be mapped in the literature (Tahsin et al., 2023). Considering the role of ICT in enabling and supporting patients with chronic diseases (Tahsin et al., 2023) and its innovative impact on the provision of health services and quality of life (Achampong, 2012), as well as the increasing growth of chronic diseases, it is necessary to design a tool to measure the use of ICT in patients suffering from chronic diseases. Based on this, the present study develops a scale for the use of ICT in patients with chronic conditions and evaluates its psychometric properties. The results of the survey based on such a tool can provide health policymakers with valuable evidence for planning and providing health care using ICT. 

Materials and Methods 

Study design, setting, and sample 
This exploratory sequential mixed-method study was conducted in two consecutive stages in Kashan Province, Iran, in 2021. The participants consisted of patients with chronic conditions, such as ischemic heart disease, diabetes, hypothyroidism, hypertension, multiple sclerosis, and cancer. The inclusion criteria were having 20 years of age or more, the ability to verbally communicate with the researcher, a definite diagnosis of chronic disease by an expert, the ability to read and write, and the willingness to participate in the study. 

First stage 
During the first phase, a qualitative study was conducted with patients referred to internal wards of Shahid Beheshti Hospital and private centers serving patients with chronic diseases in Kashan Province, Iran. A total of 18 patients with chronic diseases were selected based on the purposive sampling method and the data were collected through semi-structured face-to-face interviews. The main interview questions were as follows: 1) “Explain what using technology means to you.” and 2) “Explain how health-related technologies can help you.” The interviews were conducted after coordination with the patients in private rooms of the research environment and each session lasted approximately 20 to 30 min. With the consent of the participants, the interviews were recorded using a digital audio recorder. The data collection continued until data saturation and no new code generation occurred (Braun & Clarke, 2021). Interviews were transcribed verbatim and analyzed using conventional content analysis, and scale items were extracted using the method presented by Waltz et al. (2010). Finally, a preliminary instrument of 33 items was developed based on the interviews.

Second stage
In the second step, psychometric tests of the primary instrument were performed. To determine the quantitative face validity of the tool, 10 patients with chronic diseases who were referred to the internal wards of Shahid Beheshti Hospital filled in the importance of each item on a 5-point Likert scale ranging from “not very important” to “very important”. Subsequently, impact scores for each item were calculated using the Equation 1: 
1. Impact scores=Prevalence (%)×Importance.
If items had an impact score above 1.5, the item was kept (Polit & Beck, 2010). The quantitative content validity of the tool was verified by determining the content validity ratio (CVR) and the content validity index (CVI). CVR indicates the necessity of each element on a scale (Almanasreh et al., 2019) calculated based on the Lawshe table (Lawshe, 1975). The scale was rated by 12 experts, eight of whom had PhDs in nursing with experience in tool development and four were experts in medical information technology. Experts identified the necessity of each item on a 3-point Likert scale (from 1=not necessary, 2=useful but not necessary, 3=necessary). The CVR of each subject was then calculated. To assess the CVI, the tool was administered to the same experts and asked to rate the importance of each item on a 4-point Likert scale (ranging from 1=not important to 4=completely important). Modified Kappa values ​​were then estimated.
According to Polit & Beck, (2010), the modified Kappa values were as follows: Fair=0.40-0.59, good=0.6 to 0.74, and excellent k >0.74. To measure the CVI of the scale, the average of the content validity indices of all items was calculated. Items with a score of <0.70 were not considered acceptable and were removed. Items with scores >0.79 were considered appropriate and items with scores between 0.79 and 0.70 were modified (Polit & Beck, 2010).
To assess qualitative content validity, the scale was administered to 12 experts who provided opinions on grammar, wording, item alignment, scaling, clarity, and simplicity. Finally, by removing 2 items in the face validity phase and 3 items in the content validity phase, a 28-item construct validity scale was produced. Exploratory factor analysis (EFA) was used to assess the construct validity of the scale (Taherdoost et al., 2022). For this purpose, the scale was given to 300 patients with chronic diseases to complete it. These patients were recruited by sequential sampling. The number of samples needed to perform EFA varies from the perspective of different researchers. The minimum sample size for each item was 5-10 subjects (Nguyen & Waller, 2022). In this study, 10 subjects (280 patients) were considered for each item; however, 300 questionnaires were completed to reduce the possibility of error. After obtaining the necessary consent, the patients were selected based on the inclusion criteria and completed a questionnaire on demographic characteristics and the developed scale. EFA was performed using principal component analysis with varimax rotation.
To determine the factors, an eigenvalue greater than 1.0 and for removing items a factor loading lower than 0.4 were considered. Meanwhile, 5 items with factor loadings <0.4 were removed, resulting in item reduction.
The internal consistency of the scale and its subscales was calculated using the Cronbach α coefficient (Alkhadim, 2022). The test re-test method was used to measure the stability of the scale. The scale was administered to 15 chronically ill patients twice at two-week intervals, and the correlation coefficient between the results of the two tests was calculated (Ten Hove et al., 2022).

Data analysis
Data analysis was performed using the SPSS software, version 16. The normality of quantitative data was performed using the Kolmogorov-Smirnov test. Descriptive statistics, including frequency, Mean±SD, variance, and range of scores were used to summarize the study patients’ characteristics. The Bartlett test of sphericity and the Kaiser-Meyer Olkin test of goodness of fit were used to determine the suitability of data for exploratory factor analysis. All analyses considered a significance level of <0.05.

3. Results 
The initial version of the scale had 33 items in four domains as follows; familiarity with ICT (6 items), access to ICT (6 items), receive of services (14 items), and health information seeking (7 items). Examining the impact scores of the items revealed that two items scored below 1.5 and were removed from the tool. 
Assessing the quantitative content validity, the CVR of the two items (0.56) was lower than the indicator of Lawshe and these items were also removed. Examining the item CVI revealed that one item had a score below 0.70 and was removed. 
The scale CVI average was 0.91. Overall, a preliminary version of the 28-item tool was produced during the first phase of psychometric evaluation with modifications to determine construct validity.
The analysis of the demographic characteristics of the 300 patients showed that the subjects ranged in age from 20 to 85 years, with a mean age of 44.57±9.59 years, which is summarized in Table 1.



Based on the Kaiser-Meyer Olkin test (0.85), the sample size was adequate, and the Bartlett test also showed that the correlation matrix between the items of the scale did not interfere with factor analysis. The factor analysis identified four factors, removing 4 items with factor loadings <0.4 and one item with cross-factor loadings. These factors were named under the titles of familiarity with ICT, access to ICT, receiving of services, and health information seeking, which explained 67.45% of the variance of the tool’s total score (Table 2).



The internal consistency of the scale was assessed using the Cronbach α method at 0.93. The Cronbach α coefficients for the subscales were calculated between 0.84 and 0.94 (Table 3). The scale stability was calculated by test re-test (0.88). The intraclass correlation coefficient for subscales ranged from 0.77 to 0.81 (Table 3). Finally, a 23-item, four-factor instrument was developed, rated on a 5-point Likert scale.



Scoring of the subscale of familiarity with ICT was as follows: Very much=4, much=3, somewhat=2, little=1, and not at all=0. Other subscales (health Information seeking, receiving services, and access to ICT) were scored as follows: Always=4, often=3, sometimes=2, rarely=1, and never=0. To calculate the total score of the scale, the scores of each item were summed. The minimum and maximum points of the scale were 0 to 112, respectively. Higher scores indicated better use of ICT (Table 3). A summary of the stages of the study and its results are presented in Table 4.



Discussion 
This study developed an instrument to measure the use of ICT by patients suffering from chronic diseases. The results showed that the developed scale is a valid and reliable tool with four subscales that include health information seeking (5 points), receiving services (7 points), familiarity with ICT (6 points), and access to ICT used by the Iranian population (5 items). The present study has highlighted that two factors of health information-seeking and receiving services have the highest factor load among the four factors of using ICT. Simultaneously, the other two factors of familiarity with ICT and access to ICT are less important in the use of ICT. 
The importance of these factors is highlighted by some similarities and differences in previous studies. In line with our results, other studies in Iran and Spain demonstrated that most patients use ICT for health information seeking and receiving education (Alarcon et al., 2006; Zare & Jebraeily, 2018). In the present study, the health information seeking of patients was focused on the type and intensity of physical activity, dietary guidelines, and the side effects of the drugs used, which is consistent with the results of other studies (Apolinário-Hagen et al., 2017; Frontini & Sousa, 2019). However, a study in Portugal showed that the most important reason for patients to use ICT was to receive services, such as receiving test results, renewing prescriptions, instructions about treatment, and receiving information about how to take their medications (Santana, 2007). Another study stated that the most important reason for the willingness of patients to use ICT were having independence, managing chronic conditions, and having access to health information sources at any time and place (Vassli & Farshchian, 2018). 
ICT is an important technology for patients to communicate with health resources and receive health care, but its acceptance is influenced by the variables of perceived usefulness, ease of use, and attitude (AlQudah et al., 2021; Nazari-Shirkouhi et al., 2023; Tabares-Tabares et al., 2020; Zin et al., 2023). These features are consistent with what was found in the present study. 
The internal consistency of the whole scale was 0.93. According to Nawi et al. (2020), the internal consistency of higher than 0.90 indicates that some items may be redundant (Nawi et al., 2020). Therefore, a confirmatory factor analysis is suggested. This method shows whether the number of items in a structure is correctly selected. In other words, it determines the appropriateness of each item in a factor (Brown, 2015). 

Conclusion 
The developed scale with subscales of health information seeking, receiving services, familiarity with ICT, and access to ICT is a valid and reliable tool for measuring the use of ICT by patients with chronic diseases. Developed as a research tool, the scale provides healthcare professionals with the information needed to identify digital health challenges for patients with chronic diseases. 
Therefore, the current scale is a cost-effective way to grow health-related knowledge and improve self-care in patients with chronic conditions.
The findings should be interpreted cautiously because there are limitations in the scale in the qualitative and quantitative phases of development. The data were collected by self-reporting and non-probability sampling methods were used to select the participants; therefore, the sample may not be representative of all patients with chronic conditions. Accordingly, further studies are required to evaluate the reliability and stability of the scale and its structure validity in different regions. Due to the relatively small geographical area in which the data were collected, the wider generalization of the present results may be limited.

Ethical Considerations

Compliance with ethical guidelines
This study was approved by the Ethics Committee of Kashan University of Medical Sciences (Code: IR.KAUMS.NUHEPM.REC.1399.041). All the participants were assured about the anonymity and confidentiality of information and audio files. Written informed consent was obtained from the participants.

Funding
This study was financially supported by Kashan University of Medical Sciences, Iran (Grant No.: 99096).

Authors' contributions
Methodology: Fatemeh Sadat Izadi-Avanji; Conceptualization, supervision Investigation, writing: All authors

Conflict of interest
The authors declared no conflict of interest.

Acknowledgments
The authors express their gratitude to Kashan University of Medical Sciences.


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